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ORCID33rd AAAI 2019: Honolulu, Hawaii, USA
- The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019. AAAI Press 2019, ISBN 978-1-57735-809-1
AAAI Technical Track: AI and the Web
- Avinash Balakrishnan, Djallel Bouneffouf, Nicholas Mattei, Francesca Rossi:
Incorporating Behavioral Constraints in Online AI Systems. 3-11 - Sambaran Bandyopadhyay, Lokesh Nagalapatti, M. Narasimha Murty:
Outlier Aware Network Embedding for Attributed Networks. 12-19 - Umanga Bista, Alexander Patrick Mathews, Minjeong Shin, Aditya Krishna Menon, Lexing Xie
:
Comparative Document Summarisation via Classification. 20-28 - Jiaoyan Chen, Ernesto Jiménez-Ruiz, Ian Horrocks, Charles Sutton:
ColNet: Embedding the Semantics of Web Tables for Column Type Prediction. 29-36 - Jin Chen, Defu Lian, Kai Zheng:
Improving One-Class Collaborative Filtering via Ranking-Based Implicit Regularizer. 37-44 - Long Chen, Ziyu Guan, Wei Zhao, Wanqing Zhao, Xiaopeng Wang, Zhou Zhao, Huan Sun:
Answer Identification from Product Reviews for User Questions by Multi-Task Attentive Networks. 45-52 - Xu Chen, Yongfeng Zhang, Zheng Qin:
Dynamic Explainable Recommendation Based on Neural Attentive Models. 53-60 - Zhi-Hong Deng, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System. 61-68 - Haoyu Dong, Shijie Liu, Shi Han, Zhouyu Fu, Dongmei Zhang:
TableSense: Spreadsheet Table Detection with Convolutional Neural Networks. 69-76 - Tiansi Dong, Zhigang Wang, Juanzi Li, Christian Bauckhage, Armin B. Cremers:
Triple Classification Using Regions and Fine-Grained Entity Typing. 77-85 - Zi-Yi Dou, Zhaopeng Tu, Xing Wang, Longyue Wang, Shuming Shi, Tong Zhang:
Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement. 86-93 - Wenjing Fu, Zhaohui Peng, Senzhang Wang, Yang Xu, Jin Li:
Deeply Fusing Reviews and Contents for Cold Start Users in Cross-Domain Recommendation Systems. 94-101 - Xiaolong Gong, Linpeng Huang, Fuwei Wang:
Feature Sampling Based Unsupervised Semantic Clustering for Real Web Multi-View Content. 102-109 - Tao Gui, Liang Zhu, Qi Zhang, Minlong Peng, Xu Zhou, Keyu Ding, Zhigang Chen:
Cooperative Multimodal Approach to Depression Detection in Twitter. 110-117 - Jun Guo, Jiahui Ye:
Anchors Bring Ease: An Embarrassingly Simple Approach to Partial Multi-View Clustering. 118-125 - Zhizhong Han, Mingyang Shang, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker:
Y2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences. 126-133 - Shizhu He, Kang Liu, Weiting An:
Learning to Align Question and Answer Utterances in Customer Service Conversation with Recurrent Pointer Networks. 134-141 - Ryu Iida, Canasai Kruengkrai, Ryo Ishida, Kentaro Torisawa, Jong-Hoon Oh, Julien Kloetzer:
Exploiting Background Knowledge in Compact Answer Generation for Why-Questions. 142-151 - Di Jin, Ziyang Liu, Weihao Li, Dongxiao He, Weixiong Zhang:
Graph Convolutional Networks Meet Markov Random Fields: Semi-Supervised Community Detection in Attribute Networks. 152-159 - Di Jin, Xinxin You, Weihao Li, Dongxiao He, Peng Cui, Françoise Fogelman-Soulié, Tanmoy Chakraborty:
Incorporating Network Embedding into Markov Random Field for Better Community Detection. 160-167 - Ricky Laishram, Jeremy D. Wendt, Sucheta Soundarajan:
Crawling the Community Structure of Multiplex Networks. 168-175 - Chao Li, Cheng Deng, Lei Wang, De Xie, Xianglong Liu:
Coupled CycleGAN: Unsupervised Hashing Network for Cross-Modal Retrieval. 176-183 - Xiaoming Li, Hui Fang, Jie Zhang:
Supervised User Ranking in Signed Social Networks. 184-191 - Zeyu Li, Jyun-Yu Jiang, Yizhou Sun, Wei Wang:
Personalized Question Routing via Heterogeneous Network Embedding. 192-199 - Dongliang Liao, Jin Xu, Gongfu Li, Weijie Huang, Weiqing Liu, Jing Li:
Popularity Prediction on Online Articles with Deep Fusion of Temporal Process and Content Features. 200-207 - Chenghao Liu, Xin Wang, Tao Lu, Wenwu Zhu, Jianling Sun, Steven C. H. Hoi:
Discrete Social Recommendation. 208-215 - Jiaqi Ma, Zhe Zhao, Jilin Chen, Ang Li, Lichan Hong, Ed H. Chi:
SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning. 216-223 - Fandong Meng, Jinchao Zhang:
DTMT: A Novel Deep Transition Architecture for Neural Machine Translation. 224-231 - Jinfeng Rao, Wei Yang, Yuhao Zhang, Ferhan Türe, Jimmy Lin:
Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search. 232-240 - Shuo Ren, Zhirui Zhang, Shujie Liu, Ming Zhou, Shuai Ma:
Unsupervised Neural Machine Translation with SMT as Posterior Regularization. 241-248 - Jiaming Shen, Ruiliang Lyu, Xiang Ren, Michelle Vanni, Brian M. Sadler, Jiawei Han:
Mining Entity Synonyms with Efficient Neural Set Generation. 249-256 - Atanu R. Sinha, Deepali Jain, Nikhil Sheoran, Sopan Khosla, Reshmi Sasidharan:
Surveys without Questions: A Reinforcement Learning Approach. 257-264 - Jiankai Sun, Bortik Bandyopadhyay, Armin Bashizade, Jiongqian Liang, P. Sadayappan, Srinivasan Parthasarathy:
ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation. 265-272 - Xiaoxiao Sun, Liyi Chen, Jufeng Yang:
Learning from Web Data Using Adversarial Discriminative Neural Networks for Fine-Grained Classification. 273-280 - Kunihiro Takeoka, Masafumi Oyamada, Shinji Nakadai, Takeshi Okadome:
Meimei: An Efficient Probabilistic Approach for Semantically Annotating Tables. 281-288 - Zhiwen Tang, Grace Hui Yang:
DeepTileBars: Visualizing Term Distribution for Neural Information Retrieval. 289-296 - Bayu Distiawan Trisedya, Jianzhong Qi, Rui Zhang:
Entity Alignment between Knowledge Graphs Using Attribute Embeddings. 297-304 - Quoc-Tuan Truong, Hady W. Lauw:
VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis. 305-312 - Chun-Hsiang Wang, Kang-Chun Fan, Chuan-Ju Wang, Ming-Feng Tsai:
UGSD: User Generated Sentiment Dictionaries from Online Customer Reviews. 313-320 - Yingkui Wang, Di Jin, Katarzyna Musial, Jianwu Dang:
Community Detection in Social Networks Considering Topic Correlations. 321-328 - Zhuo Wang, Weiping Wang, Chaokun Wang, Xiaoyan Gu, Bo Li, Dan Meng:
Community Focusing: Yet Another Query-Dependent Community Detection. 329-337 - Hong Wen, Jing Zhang, Quan Lin, Keping Yang, Pipei Huang:
Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System. 338-345 - Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, Tieniu Tan:
Session-Based Recommendation with Graph Neural Networks. 346-353 - Jing Xiao, Liang Liao, Qiegen Liu, Ruimin Hu:
CISI-net: Explicit Latent Content Inference and Imitated Style Rendering for Image Inpainting. 354-362 - Haitao Xiong, Hongfu Liu, Bineng Zhong, Yun Fu:
Structured and Sparse Annotations for Image Emotion Distribution Learning. 363-370 - Nan Xu, Wenji Mao, Guandan Chen:
Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis. 371-378 - Peng Xu, Zhaohong Deng, Kup-Sze Choi, Longbing Cao, Shitong Wang:
Multi-View Information-Theoretic Co-Clustering for Co-Occurrence Data. 379-386 - Baosong Yang, Jian Li, Derek F. Wong, Lidia S. Chao, Xing Wang, Zhaopeng Tu:
Context-Aware Self-Attention Networks. 387-394 - Xiao Yang, Madian Khabsa, Miaosen Wang, Wei Wang, Ahmed Hassan Awadallah, Daniel Kifer, C. Lee Giles:
Adversarial Training for Community Question Answer Selection Based on Multi-Scale Matching. 395-402 - Xun Yang, Yunshan Ma, Lizi Liao, Meng Wang, Tat-Seng Chua:
TransNFCM: Translation-Based Neural Fashion Compatibility Modeling. 403-410 - Qian Yu, Wai Lam:
Data Augmentation Based on Adversarial Autoencoder Handling Imbalance for Learning to Rank. 411-418 - Yujin Yuan, Liyuan Liu, Siliang Tang, Zhongfei Zhang, Yueting Zhuang, Shiliang Pu, Fei Wu, Xiang Ren:
Cross-Relation Cross-Bag Attention for Distantly-Supervised Relation Extraction. 419-426 - Qi Zeng, Liangchen Luo, Wenhao Huang, Yang Tang:
Text Assisted Insight Ranking Using Context-Aware Memory Network. 427-434 - Jing Zhang, Bowen Hao, Bo Chen, Cuiping Li, Hong Chen, Jimeng Sun:
Hierarchical Reinforcement Learning for Course Recommendation in MOOCs. 435-442 - Zhirui Zhang, Shuangzhi Wu, Shujie Liu, Mu Li, Ming Zhou, Tong Xu:
Regularizing Neural Machine Translation by Target-Bidirectional Agreement. 443-450 - Yang Zhao, Jiajun Zhang, Chengqing Zong, Zhongjun He, Hua Wu:
Addressing the Under-Translation Problem from the Entropy Perspective. 451-458 - Yu-Hang Zhou, Chen Liang, Nan Li, Cheng Yang, Shenghuo Zhu, Rong Jin:
Robust Online Matching with User Arrival Distribution Drift. 459-466
AAAI Technical Track: AI for Social Impact
- Sheila Alemany, Jonathan Beltran, Adrián Pérez, Sam Ganzfried:
Predicting Hurricane Trajectories Using a Recurrent Neural Network. 468-475 - Johan Bjorck, Brendan H. Rappazzo, Di Chen, Richard Bernstein, Peter H. Wrege, Carla P. Gomes:
Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant. 476-484 - Cen Chen, Kenli Li, Sin G. Teo, Xiaofeng Zou, Kang Wang, Jie Wang, Zeng Zeng:
Gated Residual Recurrent Graph Neural Networks for Traffic Prediction. 485-492 - Di Chen, Carla P. Gomes:
Bias Reduction via End-to-End Shift Learning: Application to Citizen Science. 493-500 - Gianlorenzo D'Angelo, Martin Olsen, Lorenzo Severini:
Coverage Centrality Maximization in Undirected Networks. 501-508 - Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic:
Bayesian Fairness. 509-516 - Wenzheng Feng, Jie Tang, Tracy Xiao Liu:
Understanding Dropouts in MOOCs. 517-524 - Meir Friedenberg, Joseph Y. Halpern:
Blameworthiness in Multi-Agent Settings. 525-532 - Serge Gaspers, Kamran Najeebullah:
Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length. 533-540 - Partha Ghosh, Arpan Losalka, Michael J. Black:
Resisting Adversarial Attacks Using Gaussian Mixture Variational Autoencoders. 541-548 - Paul Gölz, Ariel D. Procaccia:
Migration as Submodular Optimization. 549-556 - Tomer Golany, Kira Radinsky:
PGANs: Personalized Generative Adversarial Networks for ECG Synthesis to Improve Patient-Specific Deep ECG Classification. 557-564 - Josiah P. Hanna, Guni Sharon, Stephen D. Boyles, Peter Stone:
Selecting Compliant Agents for Opt-in Micro-Tolling. 565-572 - Léo Hemamou, Ghazi Felhi, Vincent Vandenbussche, Jean-Claude Martin, Chloé Clavel:
HireNet: A Hierarchical Attention Model for the Automatic Analysis of Asynchronous Video Job Interviews. 573-581 - Hao Huang, Qian Yan, Ting Gan, Di Niu, Wei Lu, Yunjun Gao:
Learning Diffusions without Timestamps. 582-589 - Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Christopher Chute, Henrik Marklund, Behzad Haghgoo, Robyn L. Ball, Katie S. Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, Andrew Y. Ng:
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. 590-597 - Songlei Jian, Liang Hu, Longbing Cao, Kai Lu, Hang Gao:
Evolutionarily Learning Multi-Aspect Interactions and Influences from Network Structure and Node Content. 598-605 - Muhammad Raza Khan, Joshua E. Blumenstock:
Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty. 606-613 - Arash Khodadadi, Daniel J. McDonald:
Algorithms for Estimating Trends in Global Temperature Volatility. 614-621 - Amanda R. Kube, Sanmay Das, Patrick J. Fowler:
Allocating Interventions Based on Predicted Outcomes: A Case Study on Homelessness Services. 622-629 - Sawan Kumar, Varsha Sreenivasan, Partha P. Talukdar, Franco Pestilli, Devarajan Sridharan:
ReAl-LiFE: Accelerating the Discovery of Individualized Brain Connectomes on GPUs. 630-638 - Chenchen Li, Xiang Yan, Xiaotie Deng, Yuan Qi, Wei Chu, Le Song, Junlong Qiao, Jianshan He, Junwu Xiong:
Latent Dirichlet Allocation for Internet Price War. 639-646 - Mike Li, Elija Perrier, Chang Xu:
Deep Hierarchical Graph Convolution for Election Prediction from Geospatial Census Data. 647-654 - Shuailong Liang, Olivia Nicol, Yue Zhang:
Who Blames Whom in a Crisis? Detecting Blame Ties from News Articles Using Neural Networks. 655-662 - Matt Olfat, Anil Aswani:
Convex Formulations for Fair Principal Component Analysis. 663-670 - Victor R. Martinez, Krishna Somandepalli, Karan Singla, Anil Ramakrishna, Yalda T. Uhls, Shrikanth S. Narayanan:
Violence Rating Prediction from Movie Scripts. 671-678 - Bowen Pan, Shangfei Wang, Qisheng Jiang:
Image Aesthetic Assessment Assisted by Attributes through Adversarial Learning. 679-686 - Hae Won Park, Ishaan Grover, Samuel Spaulding, Louis Gomez, Cynthia Breazeal:
A Model-Free Affective Reinforcement Learning Approach to Personalization of an Autonomous Social Robot Companion for Early Literacy Education. 687-694 - Hanan Rosemarin, Ariel Rosenfeld, Sarit Kraus:
Emergency Department Online Patient-Caregiver Scheduling. 695-701 - Tim G. J. Rudner, Marc Rußwurm, Jakub Fil, Ramona Pelich, Benjamin Bischke, Veronika Kopacková, Piotr Bilinski:
Multi3Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery. 702-709 - Tavpritesh Sethi, Anant Mittal, Shubham Maheshwari, Samarth Chugh:
Learning to Address Health Inequality in the United States with a Bayesian Decision Network. 710-717 - Jakub Sliwinski, Martin Strobel, Yair Zick:
Axiomatic Characterization of Data-Driven Influence Measures for Classification. 718-725 - Abby Stylianou, Hong Xuan, Maya Shende, Jonathan Brandt, Richard Souvenir, Robert Pless:
Hotels-50K: A Global Hotel Recognition Dataset. 726-733 - Ruangsak Trakunphutthirak, Yen Cheung, Vincent C. S. Lee:
A Study of Educational Data Mining: Evidence from a Thai University. 734-741 - Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng:
AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks. 742-749 - Jill-Jênn Vie, Hisashi Kashima:
Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing. 750-757 - Chaokun Wang, Junchao Zhu:
Forbidden Nodes Aware Community Search. 758-765 - Hao Wang, Chengzhi Mao, Hao He, Mingmin Zhao, Tommi S. Jaakkola, Dina Katabi:
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling. 766-773 - Fan Wu, Lixia Wu:
DeepETA: A Spatial-Temporal Sequential Neural Network Model for Estimating Time of Arrival in Package Delivery System. 774-781 - Mike Wu, Milan Mosse, Noah D. Goodman, Chris Piech:
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. 782-790 - Seunghyun Yoon, Kunwoo Park, Joongbo Shin, Hongjun Lim, Seungpil Won, Meeyoung Cha, Kyomin Jung:
Detecting Incongruity between News Headline and Body Text via a Deep Hierarchical Encoder. 791-800 - Shuaitao Zhang, Yuliang Liu, Lianwen Jin, Yaoxiong Huang, Songxuan Lai:
EnsNet: Ensconce Text in the Wild. 801-808 - Rongchang Zhao, Wangmin Liao, Beiji Zou, Zailiang Chen, Shuo Li:
Weakly-Supervised Simultaneous Evidence Identification and Segmentation for Automated Glaucoma Diagnosis. 809-816 - Sendong Zhao, Ting Liu, Sicheng Zhao, Fei Wang:
A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization. 817-824 - Ruobing Zheng, Ze Luo, Baoping Yan:
Exploiting Time-Series Image-to-Image Translation to Expand the Range of Wildlife Habitat Analysis. 825-832
AAAI Technical Track: Applications
- Karan Aggarwal, Shafiq R. Joty, Luis Fernández-Luque, Jaideep Srivastava:
Adversarial Unsupervised Representation Learning for Activity Time-Series. 834-841 - Jacob Baldwin, Ryan Burnham, Andrew Meyer, Robert Dora, Robert Wright:
Beyond Speech: Generalizing D-Vectors for Biometric Verification. 842-849 - Gissella Bejarano, David DeFazio, Arti Ramesh:
Deep Latent Generative Models for Energy Disaggregation. 850-857 - Fiammetta Caccavale, Anders Søgaard:
Predicting Concrete and Abstract Entities in Modern Poetry. 858-864 - Cheng Chen, Qi Dou, Hao Chen, Jing Qin, Pheng-Ann Heng:
Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation. 865-872 - Lisi Chen, Shuo Shang:
Region-Based Message Exploration over Spatio-Temporal Data Streams. 873-880 - Michael Dann, Fabio Zambetta, John Thangarajah:
Deriving Subgoals Autonomously to Accelerate Learning in Sparse Reward Domains. 881-889 - Zulong Diao, Xin Wang, Dafang Zhang, Yingru Liu, Kun Xie, Shaoyao He:
Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting. 890-897 - Wei Feng, Wentao Liu, Tong Li, Jing Peng, Chen Qian, Xiaolin Hu:
Turbo Learning Framework for Human-Object Interactions Recognition and Human Pose Estimation. 898-905 - Yanjie Fu, Pengyang Wang, Jiadi Du, Le Wu, Xiaolin Li:
Efficient Region Embedding with Multi-View Spatial Networks: A Perspective of Locality-Constrained Spatial Autocorrelations. 906-913 - Susobhan Ghosh, Easwar Subramanian, Sanjay P. Bhat, Sujit Gujar, Praveen Paruchuri:
VidyutVanika: A Reinforcement Learning Based Broker Agent for a Power Trading Competition. 914-921 - Shengnan Guo, Youfang Lin, Ning Feng, Chao Song, Huaiyu Wan:
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting. 922-929 - Rahul Gupta, Aditya Kanade, Shirish K. Shevade:
Deep Reinforcement Learning for Syntactic Error Repair in Student Programs. 930-937 - Yu Hao, Xien Liu, Ji Wu, Ping Lv:
Exploiting Sentence Embedding for Medical Question Answering. 938-945 - Binbin Hu, Zhiqiang Zhang, Chuan Shi, Jun Zhou, Xiaolong Li, Yuan Qi:
Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism. 946-953 - Shiyu Huang, Hang Su, Jun Zhu, Ting Chen:
Combo-Action: Training Agent For FPS Game with Auxiliary Tasks. 954-961 - Steve T. K. Jan, Joseph Messou, Yen-Chen Lin, Jia-Bin Huang, Gang Wang:
Connecting the Digital and Physical World: Improving the Robustness of Adversarial Attacks. 962-969 - Jan Karwowski, Jacek Mandziuk, Adam Zychowski, Filip Grajek, Bo An:
A Memetic Approach for Sequential Security Games on a Plane with Moving Targets. 970-977 - Hoon Kim, Kangwook Lee, Gyeongjo Hwang, Changho Suh:
Crash to Not Crash: Learn to Identify Dangerous Vehicles Using a Simulator. 978-985 - John Krumm, Eric Horvitz:
Traffic Updates: Saying a Lot While Revealing a Little. 986-995 - Chaozhuo Li, Senzhang Wang, Yukun Wang, Philip S. Yu, Yanbo Liang, Yun Liu, Zhoujun Li:
Adversarial Learning for Weakly-Supervised Social Network Alignment. 996-1003 - Youru Li, Zhenfeng Zhu, Deqiang Kong, Meixiang Xu, Yao Zhao:
Learning Heterogeneous Spatial-Temporal Representation for Bike-Sharing Demand Prediction. 1004-1011 - Zhongnian Li, Tao Zhang, Peng Wan, Daoqiang Zhang:
SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction. 1012-1019 - Ziqian Lin, Jie Feng, Ziyang Lu, Yong Li, Depeng Jin:
DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis. 1020-1027 - Aishan Liu, Xianglong Liu, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie, Dacheng Tao:
Perceptual-Sensitive GAN for Generating Adversarial Patches. 1028-1035 - Hao Liu, Ting Li, Renjun Hu, Yanjie Fu, Jingjing Gu, Hui Xiong:
Joint Representation Learning for Multi-Modal Transportation Recommendation. 1036-1043 - Xiao Liu, Xiaoting Li, Rupesh Prajapati, Dinghao Wu:
DeepFuzz: Automatic Generation of Syntax Valid C Programs for Fuzz Testing. 1044-1051 - Chengqiang Lu, Qi Liu, Chao Wang, Zhenya Huang, Peize Lin, Lixin He:
Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective. 1052-1060 - Chien-Yu Lu, Min-Xin Xue, Chia-Che Chang, Che-Rung Lee, Li Su:
Play as You Like: Timbre-Enhanced Multi-Modal Music Style Transfer. 1061-1068 - Tianle Ma, Aidong Zhang:
AffinityNet: Semi-Supervised Few-Shot Learning for Disease Type Prediction. 1069-1076 - Duncan C. McElfresh, Hoda Bidkhori, John P. Dickerson:
Scalable Robust Kidney Exchange. 1077-1084 - Dong Nie, Li Wang, Lei Xiang, Sihang Zhou, Ehsan Adeli, Dinggang Shen:
Difficulty-Aware Attention Network with Confidence Learning for Medical Image Segmentation. 1085-1092 - Yuhao Niu, Lin Gu, Feng Lu, Feifan Lv, Zongji Wang, Imari Sato, Zijian Zhang, Yangyan Xiao, Xunzhang Dai, Tingting Cheng:
Pathological Evidence Exploration in Deep Retinal Image Diagnosis. 1093-1101 - Galia Nordon, Gideon Koren, Varda Shalev, Benny Kimelfeld, Uri Shalit, Kira Radinsky:
Building Causal Graphs from Medical Literature and Electronic Medical Records. 1102-1109 - Bidisha Samanta, Abir De, Gourhari Jana, Pratim Kumar Chattaraj, Niloy Ganguly, Manuel Gomez Rodriguez:
NeVAE: A Deep Generative Model for Molecular Graphs. 1110-1117 - Patrick Schwab, Walter Karlen:
PhoneMD: Learning to Diagnose Parkinson's Disease from Smartphone Data. 1118-1125 - Junyuan Shang, Cao Xiao, Tengfei Ma, Hongyan Li, Jimeng Sun:
GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination. 1126-1133 - Weiwei Shen, Bin Wang, Jian Pu, Jun Wang:
The Kelly Growth Optimal Portfolio with Ensemble Learning. 1134-1141 - Masamichi Shimosaka, Yuta Hayakawa, Kota Tsubouchi:
Spatiality Preservable Factored Poisson Regression for Large-Scale Fine-Grained GPS-Based Population Analysis. 1142-1149 - Changho Shin, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, Wonjong Rhee:
Subtask Gated Networks for Non-Intrusive Load Monitoring. 1150-1157 - Christopher Solinas, Douglas Rebstock, Michael Buro:
Improving Search with Supervised Learning in Trick-Based Card Games. 1158-1165 - Mingfei Teng, Hengshu Zhu, Chuanren Liu, Chen Zhu, Hui Xiong:
Exploiting the Contagious Effect for Employee Turnover Prediction. 1166-1173 - Bryan Wang, Yi-Hsuan Yang:
PerformanceNet: Score-to-Audio Music Generation with Multi-Band Convolutional Residual Network. 1174-1181 - Di Wang, Jinhui Xu:
Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View. 1182-1189 - Ji Wang, Weidong Bao, Lichao Sun, Xiaomin Zhu, Bokai Cao, Philip S. Yu:
Private Model Compression via Knowledge Distillation. 1190-1197 - Mingliang Wang, Jiashuang Huang, Mingxia Liu, Daoqiang Zhang:
Functional Connectivity Network Analysis with Discriminative Hub Detection for Brain Disease Identification. 1198-1205 - Bin Wu:
Hierarchical Macro Strategy Model for MOBA Game AI. 1206-1213 - Bingzhe Wu, Xiaolu Zhang, Shiwan Zhao, Lingxi Xie, Caihong Zeng, Zhihong Liu, Guangyu Sun:
G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification. 1214-1221 - I-Chen Wu, Ti-Rong Wu, An-Jen Liu, Hung Guei, Tinghan Wei:
On Strength Adjustment for MCTS-Based Programs. 1222-1229 - Kui Xu, Zhe Wang, Jianping Shi, Hongsheng Li, Qiangfeng Cliff Zhang:
A2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes. 1230-1237 - Shuai Yang, Jiaying Liu, Wenjing Wang, Zongming Guo:
TET-GAN: Text Effects Transfer via Stylization and Destylization. 1238-1245 - Kejing Yin, Dong Qian, William K. Cheung, Benjamin C. M. Fung, Jonathan Poon:
Learning Phenotypes and Dynamic Patient Representations via RNN Regularized Collective Non-Negative Tensor Factorization. 1246-1253 - Chi Zhang, Yixin Zhu, Song-Chun Zhu:
MetaStyle: Three-Way Trade-off among Speed, Flexibility, and Quality in Neural Style Transfer. 1254-1261 - Youzhi Zhang, Qingyu Guo, Bo An, Long Tran-Thanh, Nicholas R. Jennings:
Optimal Interdiction of Urban Criminals with the Aid of Real-Time Information. 1262-1269 - Ji Zhao, Dan Peng, Chuhan Wu, Huan Chen, Meiyu Yu, Wanji Zheng, Li Ma, Hua Chai, Jieping Ye, Xiaohu Qie:
Incorporating Semantic Similarity with Geographic Correlation for Query-POI Relevance Learning. 1270-1277 - Panpan Zheng, Shuhan Yuan, Xintao Wu:
SAFE: A Neural Survival Analysis Model for Fraud Early Detection. 1278-1285 - Panpan Zheng, Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu:
One-Class Adversarial Nets for Fraud Detection. 1286-1293 - Zefang Zong, Jie Feng, Kechun Liu, Hongzhi Shi, Yong Li:
DeepDPM: Dynamic Population Mapping via Deep Neural Network. 1294-1301
AAAI Technical Track: Cognitive Modeling
- Xiaolin Wu, Xi Zhang, Xiao Shu:
Cognitive Deficit of Deep Learning in Numerosity. 1303-1310 - Yujie Wu, Lei Deng, Guoqi Li, Jun Zhu, Yuan Xie, Luping Shi:
Direct Training for Spiking Neural Networks: Faster, Larger, Better. 1311-1318 - Lei Zhang, Shengyuan Zhou, Tian Zhi, Zidong Du, Yunji Chen:
TDSNN: From Deep Neural Networks to Deep Spike Neural Networks with Temporal-Coding. 1319-1326 - Malu Zhang, Jibin Wu, Yansong Chua, Xiaoling Luo, Zihan Pan, Dan Liu, Haizhou Li:
MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons. 1327-1334
AAAI Technical Track: Cognitive Systems
- Kezhen Chen, Irina Rabkina, Matthew D. McLure, Kenneth D. Forbus:
Human-Like Sketch Object Recognition via Analogical Learning. 1336-1343 - Qiuyuan Huang, Li Deng, Dapeng Oliver Wu, Chang Liu, Xiaodong He:
Attentive Tensor Product Learning. 1344-1351 - Matthew Riemer, Tim Klinger, Djallel Bouneffouf, Michele Franceschini:
Scalable Recollections for Continual Lifelong Learning. 1352-1359 - Abhishek Sharma, Keith M. Goolsbey:
Simulation-Based Approach to Efficient Commonsense Reasoning in Very Large Knowledge Bases. 1360-1367 - Di Wang, Ah-Hwee Tan, Chunyan Miao, Ahmed A. Moustafa:
Modelling Autobiographical Memory Loss across Life Span. 1368-1375
AAAI Technical Track: Computational Sustainability
- Jiaxu Cui, Bo Yang, Xia Hu:
Deep Bayesian Optimization on Attributed Graphs. 1377-1384 - Sijie He, Xinyan Li, Vidyashankar Sivakumar, Arindam Banerjee:
Interpretable Predictive Modeling for Climate Variables with Weighted Lasso. 1385-1392 - Ling Pan, Qingpeng Cai, Zhixuan Fang, Pingzhong Tang, Longbo Huang:
A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems. 1393-1400 - Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang:
Deep Reinforcement Learning for Green Security Games with Real-Time Information. 1401-1408 - Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla:
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data. 1409-1416
AAAI Technical Track: Constraint Satisfaction and Optimization
- Sina Aghaei, Mohammad Javad Azizi, Phebe Vayanos:
Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making. 1418-1426 - Daniel Anderson, Gregor Hendel, Pierre Le Bodic, Merlin Viernickel:
Clairvoyant Restarts in Branch-and-Bound Search Using Online Tree-Size Estimation. 1427-1434 - Curtis Bright, Dragomir Z. Ðokovic, Ilias S. Kotsireas, Vijay Ganesh:
A SAT+CAS Approach to Finding Good Matrices: New Examples and Counterexamples. 1435-1442 - Quentin Cappart, Emmanuel Goutierre, David Bergman, Louis-Martin Rousseau:
Improving Optimization Bounds Using Machine Learning: Decision Diagrams Meet Deep Reinforcement Learning. 1443-1451 - Alexander Diedrich, Alexander Maier, Oliver Niggemann:
Model-Based Diagnosis of Hybrid Systems Using Satisfiability Modulo Theory. 1452-1459 - Hu Ding, Mingquan Ye:
On Geometric Alignment in Low Doubling Dimension. 1460-1467 - Aritra Dutta, Filip Hanzely, Peter Richtárik:
A Nonconvex Projection Method for Robust PCA. 1468-1476 - Eduard Eiben, Robert Ganian, Dusan Knop, Sebastian Ordyniak:
Solving Integer Quadratic Programming via Explicit and Structural Restrictions. 1477-1484 - Takuro Fukunaga, Takuya Konishi, Sumio Fujita, Ken-ichi Kawarabayashi:
Stochastic Submodular Maximization with Performance-Dependent Item Costs. 1485-1494 - Amin Hosseininasab, Willem-Jan van Hoeve, André A. Ciré:
Constraint-Based Sequential Pattern Mining with Decision Diagrams. 1495-1502 - Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang:
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. 1503-1510 - Alexey Ignatiev, Nina Narodytska, João Marques-Silva:
Abduction-Based Explanations for Machine Learning Models. 1511-1519 - Yoichi Iwata, Takuto Shigemura:
Separator-Based Pruned Dynamic Programming for Steiner Tree. 1520-1527 - Ehsan Kazemi, Liqiang Wang:
Asynchronous Delay-Aware Accelerated Proximal Coordinate Descent for Nonconvex Nonsmooth Problems. 1528-1535 - Jean-Marie Lagniez, Pierre Marquis:
A Recursive Algorithm for Projected Model Counting. 1536-1543 - Liping Li, Wei Xu, Tianyi Chen, Georgios B. Giannakis, Qing Ling:
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets. 1544-1551 - Jingchang Liu, Linli Xu, Junliang Guo, Xin Sheng:
Adaptive Proximal Average Based Variance Reducing Stochastic Methods for Optimization with Composite Regularization. 1552-1559 - Shengcai Liu, Ke Tang, Xin Yao:
Automatic Construction of Parallel Portfolios via Explicit Instance Grouping. 1560-1567 - Igor Molybog, Javad Lavaei:
On Sampling Complexity of the Semidefinite Affine Rank Feasibility Problem. 1568-1575 - Jarrid Rector-Brooks, Jun-Kun Wang, Barzan Mozafari:
Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets. 1576-1583 - Christoph Scholl, Jie-Hong Roland Jiang, Ralf Wimmer, Aile Ge-Ernst:
A PSPACE Subclass of Dependency Quantified Boolean Formulas and Its Effective Solving. 1584-1591 - Mate Soos, Kuldeep S. Meel:
BIRD: Engineering an Efficient CNF-XOR SAT Solver and Its Applications to Approximate Model Counting. 1592-1599 - Sabine Storandt, Stefan Funke:
Algorithms for Average Regret Minimization. 1600-1607 - Miguel Terra-Neves, Nuno Machado, Inês Lynce, Vasco Manquinho:
Concurrency Debugging with MaxSMT. 1608-1616 - Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh:
Bayesian Functional Optimisation with Shape Prior. 1617-1624 - Sicco Verwer, Yingqian Zhang:
Learning Optimal Classification Trees Using a Binary Linear Program Formulation. 1625-1632 - Pengfei Wang, Risheng Liu, Nenggan Zheng, Zhefeng Gong:
Asynchronous Proximal Stochastic Gradient Algorithm for Composition Optimization Problems. 1633-1640 - Po-Wei Wang, J. Zico Kolter:
Low-Rank Semidefinite Programming for the MAX2SAT Problem. 1641-1649 - Yiyang Wang, Risheng Liu, Long Ma, Xiaoliang Song:
Task Embedded Coordinate Update: A Realizable Framework for Multivariate Non-Convex Optimization. 1650-1657 - Bryan Wilder, Bistra Dilkina, Milind Tambe:
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization. 1658-1665 - Jiacheng Wu, Jian-Xun Wang, Shawn C. Shadden:
Adding Constraints to Bayesian Inverse Problems. 1666-1673 - Qiao Xiang, Haitao Yu, James Aspnes, Franck Le, Linghe Kong, Yang Richard Yang:
Optimizing in the Dark: Learning an Optimal Solution through a Simple Request Interface. 1674-1681 - Xiaoyong Yuan, Zheng Feng, Matthew Norton, Xiaolin Li:
Generalized Batch Normalization: Towards Accelerating Deep Neural Networks. 1682-1689
AAAI Technical Track: Game Playing and Interactive Entertainment
- Raluca D. Gaina, Simon M. Lucas, Diego Pérez-Liébana:
Tackling Sparse Rewards in Real-Time Games with Statistical Forward Planning Methods. 1691-1698 - Jakub Kowalski, Maksymilian Mika, Jakub Sutowicz, Marek Szykula:
Regular Boardgames. 1699-1706 - Yining Lang, Wei Liang, Yujia Wang, Lap-Fai Yu:
3D Face Synthesis Driven by Personality Impression. 1707-1714 - Juntao Li, Lidong Bing, Lisong Qiu, Dongmin Chen, Dongyan Zhao, Rui Yan:
Learning to Write Stories with Thematic Consistency and Wording Novelty. 1715-1722
AAAI Technical Track: Game Theory and Economic Paradigms
- Colleen Alkalay-Houlihan, Nisarg Shah:
The Pure Price of Anarchy of Pool Block Withholding Attacks in Bitcoin Mining. 1724-1731 - Eshwar Ram Arunachaleswaran, Siddharth Barman, Nidhi Rathi:
Fair Division with a Secretive Agent. 1732-1739 - Haris Aziz, Péter Biró, Ronald de Haan, Baharak Rastegari:
Pareto Optimal Allocation under Compact Uncertain Preferences. 1740-1747 - Siddharth Barman, Sanath Kumar Krishnamurthy:
On the Proximity of Markets with Integral Equilibria. 1748-1755 - Nathanaël Barrot, Kazunori Ota, Yuko Sakurai, Makoto Yokoo:
Unknown Agents in Friends Oriented Hedonic Games: Stability and Complexity. 1756-1763 - Dorothea Baumeister, Tobias Hogrebe, Lisa Rey:
Generalized Distance Bribery. 1764-1771 - Omer Ben-Porat, Gregory Goren, Itay Rosenberg, Moshe Tennenholtz:
From Recommendation Systems to Facility Location Games. 1772-1779 - Omer Ben-Porat, Itay Rosenberg, Moshe Tennenholtz:
Convergence of Learning Dynamics in Information Retrieval Games. 1780-1787 - Gerdus Benadè, Ariel D. Procaccia, Mingda Qiao:
Low-Distortion Social Welfare Functions. 1788-1795 - Daan Bloembergen, Davide Grossi, Martin Lackner:
On Rational Delegations in Liquid Democracy. 1796-1803 - Allan Borodin, Omer Lev, Nisarg Shah, Tyrone Strangway:
Primarily about Primaries. 1804-1811 - Simina Brânzei, Aris Filos-Ratsikas:
Walrasian Dynamics in Multi-Unit Markets. 1812-1819 - Gianluca Brero, Sébastien Lahaie, Sven Seuken:
Fast Iterative Combinatorial Auctions via Bayesian Learning. 1820-1828 - Noam Brown, Tuomas Sandholm:
Solving Imperfect-Information Games via Discounted Regret Minimization. 1829-1836 - Sofia Ceppi, Ian A. Kash, Rafael M. Frongillo:
Partial Verification as a Substitute for Money. 1837-1844 - Yiling Chen, Yang Liu, Juntao Wang:
Randomized Wagering Mechanisms. 1845-1852 - Vincent Conitzer, Rupert Freeman, Nisarg Shah, Jennifer Wortman Vaughan:
Group Fairness for the Allocation of Indivisible Goods. 1853-1860 - Trevor Davis, Kevin Waugh, Michael Bowling:
Solving Large Extensive-Form Games with Strategy Constraints. 1861-1868 - Ilias Diakonikolas, Chrystalla Pavlou:
On the Complexity of the Inverse Semivalue Problem for Weighted Voting Games. 1869-1876 - John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu:
Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity. 1877-1884 - Hossein Esfandiari, Mohammad Taghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher:
Online Pandora's Boxes and Bandits. 1885-1892 - Brandon Fain, Ashish Goel, Kamesh Munagala, Nina Prabhu:
Random Dictators with a Random Referee: Constant Sample Complexity Mechanisms for Social Choice. 1893-1900 - Piotr Faliszewski, Pasin Manurangsi, Krzysztof Sornat:
Approximation and Hardness of Shift-Bribery. 1901-1908 - Piotr Faliszewski, Piotr Skowron, Arkadii Slinko, Stanislaw Szufa, Nimrod Talmon:
How Similar Are Two Elections? 1909-1916 - Gabriele Farina, Christian Kroer, Tuomas Sandholm:
Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games. 1917-1925 - Michail Fasoulakis, Evangelos Markakis:
An Improved Quasi-Polynomial Algorithm for Approximate Well-Supported Nash Equilibria. 1926-1932 - Zack Fitzsimmons, Edith Hemaspaandra, Alexander Hoover, David E. Narváez:
Very Hard Electoral Control Problems. 1933-1940 - Till Fluschnik, Piotr Skowron, Mervin Triphaus, Kai Wilker:
Fair Knapsack. 1941-1948 - Dimitris Fotakis, Kyriakos Lotidis, Chara Podimata:
A Bridge between Liquid and Social Welfare in Combinatorial Auctions with Submodular Bidders. 1949-1956 - Rupert Freeman, David M. Pennock, Jennifer Wortman Vaughan:
An Equivalence between Wagering and Fair-Division Mechanisms. 1957-1964 - Eric J. Friedman, Vasilis Gkatzelis, Christos-Alexandros Psomas, Scott Shenker:
Fair and Efficient Memory Sharing: Confronting Free Riders. 1965-1972 - Matthias Gerstgrasser, Paul W. Goldberg, Bart de Keijzer, Philip Lazos, Alexander Skopalik:
Multi-Unit Bilateral Trade. 1973-1980 - Mohammad Ghodsi, Mohamad Latifian, Masoud Seddighin:
On the Distortion Value of the Elections with Abstention. 1981-1988 - Gagan Goel, Vahab S. Mirrokni, Renato Paes Leme:
Pareto Efficient Auctions with Interest Rates. 1989-1995 - Naman Goel, Boi Faltings:
Deep Bayesian Trust: A Dominant and Fair Incentive Mechanism for Crowd. 1996-2003 - Sreenivas Gollapudi, Kostas Kollias, Debmalya Panigrahi:
You Get What You Share: Incentives for a Sharing Economy. 2004-2011 - Joachim Gudmundsson, Sampson Wong:
Computing the Yolk in Spatial Voting Games without Computing Median Lines. 2012-2019 - Qingyu Guo, Jiarui Gan, Fei Fang, Long Tran-Thanh, Milind Tambe, Bo An:
On the Inducibility of Stackelberg Equilibrium for Security Games. 2020-2028 - Karel Horák, Branislav Bosanský:
Solving Partially Observable Stochastic Games with Public Observations. 2029-2036 - Sen Huang, Mingyu Xiao:
Object Reachability via Swaps along a Line. 2037-2044 - Ayumi Igarashi, Dominik Peters:
Pareto-Optimal Allocation of Indivisible Goods with Connectivity Constraints. 2045-2052 - Ayumi Igarashi, Jakub Sliwinski, Yair Zick:
Forming Probably Stable Communities with Limited Interactions. 2053-2060 - Batya Kenig, Benny Kimelfeld:
Approximate Inference of Outcomes in Probabilistic Elections. 2061-2068 - Omer Lev, Yoad Lewenberg:
"Reverse Gerrymandering": Manipulation in Multi-Group Decision Making. 2069-2076 - Omer Lev, Reshef Meir, Svetlana Obraztsova, Maria Polukarov:
Heuristic Voting as Ordinal Dominance Strategies. 2077-2084 - Kai Li, Dong Hao:
Cooperation Enforcement and Collusion Resistance in Repeated Public Goods Games. 2085-2092 - Zhuoshu Li, Sanmay Das:
Revenue Enhancement via Asymmetric Signaling in Interdependent-Value Auctions. 2093-2100 - Ilan Lobel, Renato Paes Leme:
Dynamic Contracting under Positive Commitment. 2101-2108 - Pasin Manurangsi, Warut Suksompong:
When Do Envy-Free Allocations Exist? 2109-2116 - Alberto Marchesi, Gabriele Farina, Christian Kroer, Nicola Gatti, Tuomas Sandholm:
Quasi-Perfect Stackelberg Equilibrium. 2117-2124 - Vahab S. Mirrokni, Renato Paes Leme, Pingzhong Tang, Song Zuo:
Optimal Dynamic Auctions Are Virtual Welfare Maximizers. 2125-2132 - Thanh Hong Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman:
Deception in Finitely Repeated Security Games. 2133-2140 - Hoon Oh, Ariel D. Procaccia, Warut Suksompong:
Fairly Allocating Many Goods with Few Queries. 2141-2148 - Binghui Peng, Weiran Shen, Pingzhong Tang, Song Zuo:
Learning Optimal Strategies to Commit To. 2149-2156 - Martin Schmid, Neil Burch, Marc Lanctot, Matej Moravcik, Rudolf Kadlec, Michael Bowling:
Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games Using Baselines. 2157-2164 - Sujoy Sikdar, Sibel Adali, Lirong Xia:
Mechanism Design for Multi-Type Housing Markets with Acceptable Bundles. 2165-2172 - Samuel Sokota, Caleb Ho, Bryce Wiedenbeck:
Learning Deviation Payoffs in Simulation-Based Games. 2173-2180 - Nimrod Talmon, Piotr Faliszewski:
A Framework for Approval-Based Budgeting Methods. 2181-2188 - Jun Wang, Sujoy Sikdar, Tyler Shepherd, Zhibing Zhao, Chunheng Jiang, Lirong Xia:
Practical Algorithms for Multi-Stage Voting Rules with Parallel Universes Tiebreaking. 2189-2196 - Tomasz Was, Talal Rahwan, Oskar Skibski:
Random Walk Decay Centrality. 2197-2204 - Anaëlle Wilczynski:
Poll-Confident Voters in Iterative Voting. 2205-2212 - Bryan Wilder, Yevgeniy Vorobeychik:
Defending Elections against Malicious Spread of Misinformation. 2213-2220 - Pan Xu, Yexuan Shi, Hao Cheng, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yongxin Tong, Leonidas Tsepenekas:
A Unified Approach to Online Matching with Conflict-Aware Constraints. 2221-2228 - Hanrui Zhang, Yu Cheng, Vincent Conitzer:
A Better Algorithm for Societal Tradeoffs. 2229-2236 - Hanrui Zhang, Vincent Conitzer:
A PAC Framework for Aggregating Agents' Judgments. 2237-2244 - Boming Zhao, Pan Xu, Yexuan Shi, Yongxin Tong, Zimu Zhou, Yuxiang Zeng:
Preference-Aware Task Assignment in On-Demand Taxi Dispatching: An Online Stable Matching Approach. 2245-2252 - Tianhang Zheng, Changyou Chen, Kui Ren:
Distributionally Adversarial Attack. 2253-2260
AAAI Technical Track: Heuristic Search and Optimization
- Junwen Ding, Zhipeng Lü, Chu-Min Li, Liji Shen, Liping Xu, Fred W. Glover:
A Two-Individual Based Evolutionary Algorithm for the Flexible Job Shop Scheduling Problem. 2262-2271 - Tobias Friedrich, Andreas Göbel, Frank Neumann, Francesco Quinzan, Ralf Rothenberger:
Greedy Maximization of Functions with Bounded Curvature under Partition Matroid Constraints. 2272-2279 - Baokun He, Swair Shah, Crystal Maung, Gordon Arnold, Guihong Wan, Haim Schweitzer:
Heuristic Search Algorithm for Dimensionality Reduction Optimally Combining Feature Selection and Feature Extraction. 2280-2287 - Robert C. Holte, Sandra Zilles:
On the Optimal Efficiency of Cost-Algebraic A. 2288-2295 - Zhengxin Huang, Yuren Zhou, Zefeng Chen, Xiaoyu He:
Running Time Analysis of MOEA/D with Crossover on Discrete Optimization Problem. 2296-2303 - Ken Kobayashi, Naoki Hamada, Akiyoshi Sannai, Akinori Tanaka, Kenichi Bannai, Masashi Sugiyama:
Bézier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-Objective Optimization. 2304-2313 - Juho Lauri, Sourav Dutta:
Fine-Grained Search Space Classification for Hard Enumeration Variants of Subset Problems. 2314-2321 - Andrei Lissovoi, Pietro S. Oliveto, John Alasdair Warwicker:
On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation. 2322-2329 - Julian R. H. Mariño, Rubens O. Moraes, Cláudio Toledo, Levi H. S. Lelis:
Evolving Action Abstractions for Real-Time Planning in Extensive-Form Games. 2330-2337 - Andrew Mitchell, Wheeler Ruml, Fabian Spaniol, Jörg Hoffmann, Marek Petrik:
Real-Time Planning as Decision-Making under Uncertainty. 2338-2345 - Frank Neumann, Andrew M. Sutton:
Evolving Solutions to Community-Structured Satisfiability Formulas. 2346-2353 - Vahid Roostapour, Aneta Neumann, Frank Neumann, Tobias Friedrich:
Pareto Optimization for Subset Selection with Dynamic Cost Constraints. 2354-2361 - Christopher D. Rosin:
Stepping Stones to Inductive Synthesis of Low-Level Looping Programs. 2362-2370 - Shahaf S. Shperberg, Andrew Coles, Bence Cserna, Erez Karpas, Wheeler Ruml, Solomon Eyal Shimony:
Allocating Planning Effort When Actions Expire. 2371-2378 - Shahaf S. Shperberg, Ariel Felner, Nathan R. Sturtevant, Solomon Eyal Shimony, Avi Hayoun:
Enriching Non-Parametric Bidirectional Search Algorithms. 2379-2386 - Markus Spies, Marco Todescato, Hannes Becker, Patrick Kesper, Nicolai Waniek, Meng Guo:
Bounded Suboptimal Search with Learned Heuristics for Multi-Agent Systems. 2387-2394 - Thomas Weise, Zijun Wu, Markus Wagner:
An Improved Generic Bet-and-Run Strategy with Performance Prediction for Stochastic Local Search. 2395-2402 - Aimin Zhou, Jinyuan Zhang, Jianyong Sun, Guixu Zhang:
Fuzzy-Classification Assisted Solution Preselection in Evolutionary Optimization. 2403-2410
AAAI Technical Track: Human-AI Collaboration
- Tameem Adel, Isabel Valera, Zoubin Ghahramani, Adrian Weller:
One-Network Adversarial Fairness. 2412-2420 - Shani Alkoby, Zihe Wang, David Sarne, Pingzhong Tang:
Making Money from What You Know - How to Sell Information? 2421-2428 - Gagan Bansal, Besmira Nushi, Ece Kamar, Daniel S. Weld, Walter S. Lasecki, Eric Horvitz:
Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff. 2429-2437 - Alvaro H. C. Correia, Freddy Lécué:
Human-in-the-Loop Feature Selection. 2438-2445 - Gil Einziger, Maayan Goldstein, Yaniv Sa'ar, Itai Segall:
Verifying Robustness of Gradient Boosted Models. 2446-2453 - Andrew Forney, Elias Bareinboim:
Counterfactual Randomization: Rescuing Experimental Studies from Obscured Confounding. 2454-2461 - Vinicius G. Goecks, Gregory M. Gremillion, Vernon J. Lawhern, John Valasek, Nicholas R. Waytowich:
Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time. 2462-2470 - Mingxuan Jing, Xiaojian Ma, Wen-bing Huang, Fuchun Sun, Huaping Liu:
Task Transfer by Preference-Based Cost Learning. 2471-2478 - Anagha Kulkarni, Siddharth Srivastava, Subbarao Kambhampati:
A Unified Framework for Planning in Adversarial and Cooperative Environments. 2479-2487 - Dongze Lian, Ziheng Zhang, Weixin Luo, Lina Hu, Minye Wu, Zechao Li, Jingyi Yu, Shenghua Gao:
RGBD Based Gaze Estimation via Multi-Task CNN. 2488-2495 - Yuzuru Okajima, Kunihiko Sadamasa:
Deep Neural Networks Constrained by Decision Rules. 2496-2505 - Linsen Song, Jie Cao, Lingxiao Song, Yibo Hu, Ran He:
Geometry-Aware Face Completion and Editing. 2506-2513 - Nicholay Topin, Manuela Veloso:
Generation of Policy-Level Explanations for Reinforcement Learning. 2514-2521 - Vaibhav V. Unhelkar, Julie A. Shah:
Learning Models of Sequential Decision-Making with Partial Specification of Agent Behavior. 2522-2530 - Loïs Vanhée, Laurent Jeanpierre, Abdel-Illah Mouaddib:
Augmenting Markov Decision Processes with Advising. 2531-2538 - Sandareka Wickramanayake, Wynne Hsu, Mong-Li Lee:
FLEX: Faithful Linguistic Explanations for Neural Net Based Model Decisions. 2539-2546 - Ziyu Yao, Xiujun Li, Jianfeng Gao, Brian M. Sadler, Huan Sun:
Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning. 2547-2554
AAAI Technical Track: Humans and AI
- Abhay M. S. Aradhya, Aditya Joglekar, Suresh Sundaram, Mahardhika Pratama:
Deep Transformation Method for Discriminant Analysis of Multi-Channel Resting State fMRI. 2556-2563 - Nan Cao, Xin Yan, Yang Shi, Chaoran Chen:
AI-Sketcher : A Deep Generative Model for Producing High-Quality Sketches. 2564-2571 - Lin Chen, Lei Xu, Shouhuai Xu, Zhimin Gao, Weidong Shi:
Election with Bribed Voter Uncertainty: Hardness and Approximation Algorithm. 2572-2579 - Xiao Guo, Jongmoo Choi:
Human Motion Prediction via Learning Local Structure Representations and Temporal Dependencies. 2580-2587 - Yaman Kumar, Rohit Jain, Khwaja Mohd. Salik, Rajiv Ratn Shah, Yifang Yin, Roger Zimmermann:
Lipper: Synthesizing Thy Speech Using Multi-View Lipreading. 2588-2595 - Keting Lu, Shiqi Zhang, Xiaoping Chen:
Goal-Oriented Dialogue Policy Learning from Failures. 2596-2603 - Rafael R. Padovani, Lucas N. Ferreira, Levi H. S. Lelis:
Be Inaccurate but Don't Be Indecisive: How Error Distribution Can Affect User Experience. 2604-2611 - Hermann Schichl, Meinolf Sellmann:
Consensual Affine Transformations for Partial Valuation Aggregation. 2612-2619 - Sicheng Zhao, Chuang Lin, Pengfei Xu, Sendong Zhao, Yuchen Guo, Ravi Krishna, Guiguang Ding, Kurt Keutzer:
CycleEmotionGAN: Emotional Semantic Consistency Preserved CycleGAN for Adapting Image Emotions. 2620-2627
AAAI Technical Track: Human-Computation and Crowd Sourcing
- Yan Zhao, Jinfu Xia, Guanfeng Liu, Han Su, Defu Lian, Shuo Shang, Kai Zheng:
Preference-Aware Task Assignment in Spatial Crowdsourcing. 2629-2636
AAAI Technical Track: Knowledge Representation and Reasoning
- Erman Acar, Massimo Benerecetti, Fabio Mogavero:
Satisfiability in Strategy Logic Can Be Easier than Model Checking. 2638-2645 - Natasha Alechina, Tomás Brázdil, Giuseppe De Giacomo, Paolo Felli, Brian Logan, Moshe Y. Vardi:
Unbounded Orchestrations of Transducers for Manufacturing. 2646-2653 - Medina Andresel, Yazmín Ibáñez-García, Magdalena Ortiz, Mantas Simkus:
Relaxing and Restraining Queries for OBDA. 2654-2661 - Alexander Bagnall, Gordon Stewart:
Certifying the True Error: Machine Learning in Coq with Verified Generalization Guarantees. 2662-2669 - Ringo Baumann, Gerhard Brewka:
Extension Removal in Abstract Argumentation - An Axiomatic Approach. 2670-2677 - Sander Beckers, Joseph Y. Halpern:
Abstracting Causal Models. 2678-2685 - Bart Bogaerts:
Weighted Abstract Dialectical Frameworks through the Lens of Approximation Fixpoint Theory. 2686-2693 - Jori Bomanson, Tomi Janhunen, Antonius Weinzierl:
Enhancing Lazy Grounding with Lazy Normalization in Answer-Set Programming. 2694-2702 - Blai Bonet, Guillem Francès, Hector Geffner:
Learning Features and Abstract Actions for Computing Generalized Plans. 2703-2710 - Stefan Borgwardt, Ismail Ilkan Ceylan, Thomas Lukasiewicz:
Ontology-Mediated Query Answering over Log-Linear Probabilistic Data. 2711-2718 - Camille Bourgaux, Ana Ozaki:
Querying Attributed DL-Lite Ontologies Using Provenance Semirings. 2719-2726 - Andreas Bunte, Benno Stein, Oliver Niggemann:
Model-Based Diagnosis for Cyber-Physical Production Systems Based on Machine Learning and Residual-Based Diagnosis Models. 2727-2735 - David Carral, Larry González, Patrick Koopmann:
From Horn-SRIQ to Datalog: A Data-Independent Transformation That Preserves Assertion Entailment. 2736-2743 - Juan D. Correa, Jin Tian, Elias Bareinboim:
Identification of Causal Effects in the Presence of Selection Bias. 2744-2751 - Kristijonas Cyras, Dimitrios Letsios, Ruth Misener, Francesca Toni:
Argumentation for Explainable Scheduling. 2752-2759 - Daniel de Leng, Fredrik Heintz:
Approximate Stream Reasoning with Metric Temporal Logic under Uncertainty. 2760-2767 - Warren Del-Pinto, Renate A. Schmidt:
ABox Abduction via Forgetting in ALC. 2768-2775 - Heshan Du, Natasha Alechina:
Qualitative Spatial Logic over 2D Euclidean Spaces Is Not Finitely Axiomatisable. 2776-2783 - Jianfeng Du, Jeff Z. Pan, Sylvia Wang, Kunxun Qi, Yuming Shen, Yu Deng:
Validation of Growing Knowledge Graphs by Abductive Text Evidences. 2784-2791 - Phan Minh Dung, Phan Minh Thang, Tran Cao Son:
On Structured Argumentation with Conditional Preferences. 2792-2800 - Wolfgang Dvorák, Stefan Woltran:
Complexity of Abstract Argumentation under a Claim-Centric View. 2801-2808 - Wolfgang Faber, Michael Morak, Stefan Woltran:
Strong Equivalence for Epistemic Logic Programs Made Easy. 2809-2816 - Liangda Fang, Kewen Wang, Zhe Wang, Ximing Wen:
Disjunctive Normal Form for Multi-Agent Modal Logics Based on Logical Separability. 2817-2826 - Johannes Klaus Fichte, Markus Hecher, Arne Meier:
Counting Complexity for Reasoning in Abstract Argumentation. 2827-2834 - Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock:
A Sequential Set Generation Method for Predicting Set-Valued Outputs. 2835-2842 - Ricardo Gonçalves, Tomi Janhunen, Matthias Knorr, João Leite, Stefan Woltran:
Forgetting in Modular Answer Set Programming. 2843-2850 - Joseph Y. Halpern, Evan Piermont:
Partial Awareness. 2851-2858 - Pan Hu, Boris Motik, Ian Horrocks:
Modular Materialisation of Datalog Programs. 2859-2866 - Xuanxiang Huang, Kehang Fang, Liangda Fang, Qingliang Chen, Zhao-Rong Lai, Linfeng Wei:
Bi-Kronecker Functional Decision Diagrams: A Novel Canonical Representation of Boolean Functions. 2867-2875 - Saravanan Kandasamy, Arnab Bhattacharyya, Vasant G. Honavar:
Minimum Intervention Cover of a Causal Graph. 2876-2885 - Phokion G. Kolaitis, Lucian Popa, Kun Qian:
Knowledge Refinement via Rule Selection. 2886-2894 - Fanshuang Kong, Richong Zhang, Yongyi Mao, Ting Deng:
LENA: Locality-Expanded Neural Embedding for Knowledge Base Completion. 2895-2902 - Patrick Koopmann:
Ontology-Based Query Answering for Probabilistic Temporal Data. 2903-2910 - Nikhil Krishnaswamy, Scott Friedman, James Pustejovsky:
Combining Deep Learning and Qualitative Spatial Reasoning to Learn Complex Structures from Sparse Examples with Noise. 2911-2918 - Mark Law, Alessandra Russo, Elisa Bertino, Krysia Broda, Jorge Lobo:
Representing and Learning Grammars in Answer Set Programming. 2919-2928 - Tiep Le, Tran Cao Son, Enrico Pontelli:
Multi-Context System for Optimization Problems. 2929-2937 - Tuomo Lehtonen, Johannes Peter Wallner, Matti Järvisalo:
Reasoning over Assumption-Based Argumentation Frameworks via Direct Answer Set Programming Encodings. 2938-2945 - Jianwen Li, Kristin Y. Rozier, Geguang Pu, Yueling Zhang, Moshe Y. Vardi:
SAT-Based Explicit LTLf Satisfiability Checking. 2946-2953 - Zi Lin, Yang Liu:
Implanting Rational Knowledge into Distributed Representation at Morpheme Level. 2954-2961 - Thomas Lukasiewicz, Enrico Malizia, Andrius Vaicenavicius:
Complexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Cardinality-Based Repairs. 2962-2969 - Daoming Lyu, Fangkai Yang, Bo Liu, Steven Gustafson:
SDRL: Interpretable and Data-Efficient Deep Reinforcement Learning Leveraging Symbolic Planning. 2970-2977 - Ke Ma, Qianqian Xu, Zhiyong Yang, Xiaochun Cao:
Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin. 2978-2985 - Takanori Maehara, Yuma Inoue:
Group Decision Diagram (GDD): A Compact Representation for Permutations. 2986-2994 - Stephanie McIntyre, Alexander Borgida, David Toman, Grant E. Weddell:
On Limited Conjunctions and Partial Features in Parameter-Tractable Feature Logics. 2995-3002 - Arindam Mitra, Peter Clark, Oyvind Tafjord, Chitta Baral:
Declarative Question Answering over Knowledge Bases Containing Natural Language Text with Answer Set Programming. 3003-3010 - Pavel Naumov, Jia Tao:
Blameworthiness in Strategic Games. 3011-3018 - Jandson S. Ribeiro, Abhaya Nayak, Renata Wassermann:
Belief Change and Non-Monotonic Reasoning Sans Compactness. 3019-3026 - Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, Yejin Choi:
ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning. 3027-3035 - Md. Kamruzzaman Sarker, Pascal Hitzler:
Efficient Concept Induction for Description Logics. 3036-3043 - Haseeb Shah, Johannes Villmow, Adrian Ulges, Ulrich Schwanecke, Faisal Shafait:
An Open-World Extension to Knowledge Graph Completion Models. 3044-3051 - Farhad Shakerin, Gopal Gupta:
Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME. 3052-3059 - Chao Shang, Yun Tang, Jing Huang, Jinbo Bi, Xiaodong He, Bowen Zhou:
End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion. 3060-3067 - Chengchao Shen, Xinchao Wang, Jie Song, Li Sun, Mingli Song:
Amalgamating Knowledge towards Comprehensive Classification. 3068-3075 - Marlo Souza, Álvaro F. Moreira, Renata Vieira:
Iterated Belief Base Revision: A Dynamic Epistemic Logic Approach. 3076-3083 - Roni Stern, Brendan Juba:
Safe Partial Diagnosis from Normal Observations. 3084-3091 - Przemyslaw Andrzej Walega, Mark Kaminski, Bernardo Cuenca Grau:
Reasoning over Streaming Data in Metric Temporal Datalog. 3092-3099 - Jun Yuan, Neng Gao, Ji Xiang:
TransGate: Knowledge Graph Embedding with Shared Gate Structure. 3100-3107 - Hao Zhang, Shuigeng Zhou, Chuanxu Yan, Jihong Guan, Xin Wang:
Recursively Learning Causal Structures Using Regression-Based Conditional Independence Test. 3108-3115 - Yizheng Zhao, Ghadah Alghamdi, Renate A. Schmidt, Hao Feng, Giorgos Stoilos, Damir Juric, Mohammad Khodadadi:
Tracking Logical Difference in Large-Scale Ontologies: A Forgetting-Based Approach. 3116-3124 - Zili Zhou, Shaowu Liu, Guandong Xu, Wu Zhang:
On Completing Sparse Knowledge Base with Transitive Relation Embedding. 3125-3132
AAAI Technical Track: Machine Learning
- David Abel, Dilip Arumugam, Kavosh Asadi, Yuu Jinnai, Michael L. Littman, Lawson L. S. Wong:
State Abstraction as Compression in Apprenticeship Learning. 3134-3142 - Karim T. Abou-Moustafa, Csaba Szepesvári:
An Exponential Tail Bound for the Deleted Estimate. 3143-3150 - Arpit Agarwal, Katharina Muelling, Katerina Fragkiadaki:
Model Learning for Look-Ahead Exploration in Continuous Control. 3151-3158 - Rami Al-Rfou, Dokook Choe, Noah Constant, Mandy Guo, Llion Jones:
Character-Level Language Modeling with Deeper Self-Attention. 3159-3166 - Scott Alfeld, Ara Vartanian, Lucas Newman-Johnson, Benjamin I. P. Rubinstein:
Attacking Data Transforming Learners at Training Time. 3167-3174 - Abdul Fatir Ansari, Harold Soh:
Hyperprior Induced Unsupervised Disentanglement of Latent Representations. 3175-3182 - Chidubem Arachie, Bert Huang:
Adversarial Label Learning. 3183-3190 - Mohammadreza Armandpour, Patrick Ding, Jianhua Z. Huang, Xia Hu:
Robust Negative Sampling for Network Embedding. 3191-3198 - Kyohei Atarashi, Subhransu Maji, Satoshi Oyama:
Random Feature Maps for the Itemset Kernel. 3199-3206 - Georgia Avarikioti, Alain Ryser, Yuyi Wang, Roger Wattenhofer:
High Dimensional Clustering with r-nets. 3207-3214 - Wissam J. Baddar, Yong Man Ro:
Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition. 3215-3223 - Christopher Bartley, Wei Liu, Mark Reynolds:
Enhanced Random Forest Algorithms for Partially Monotone Ordinal Classification. 3224-3231 - Ege Beyazit, Jeevithan Alagurajah, Xindong Wu:
Online Learning from Data Streams with Varying Feature Spaces. 3232-3239 - Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel:
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks. 3240-3247 - Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos, André L. Teixeira:
Deep Convolutional Sum-Product Networks. 3248-3255 - Xu Cai, Yang Wu, Guanbin Li, Ziliang Chen, Liang Lin:
FRAME Revisited: An Interpretation View Based on Particle Evolution. 3256-3263 - Junyu Cao, Wei Sun:
Dynamic Learning of Sequential Choice Bandit Problem under Marketing Fatigue. 3264-3271 - Miriam Cha, Youngjune L. Gwon, H. T. Kung:
Adversarial Learning of Semantic Relevance in Text to Image Synthesis. 3272-3279 - Sarath Chandar, Chinnadhurai Sankar, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio:
Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. 3280-3287 - Xiaobin Chang, Yongxin Yang, Tao Xiang, Timothy M. Hospedales:
Disjoint Label Space Transfer Learning with Common Factorised Space. 3288-3295 - Chao Chen, Zhihong Chen, Boyuan Jiang, Xinyu Jin:
Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation. 3296-3303 - Chen Chen, Haobo Wang, Weiwei Liu, Xingyuan Zhao, Tianlei Hu, Gang Chen:
Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification. 3304-3311 - Haokun Chen, Xinyi Dai, Han Cai, Weinan Zhang, Xuejian Wang, Ruiming Tang, Yuzhou Zhang, Yong Yu:
Large-Scale Interactive Recommendation with Tree-Structured Policy Gradient. 3312-3320 - Kaixuan Chen, Lina Yao, Dalin Zhang, Xiaojun Chang, Guodong Long, Sen Wang:
Distributionally Robust Semi-Supervised Learning for People-Centric Sensing. 3321-3328 - Shangyu Chen, Wenya Wang, Sinno Jialin Pan:
Deep Neural Network Quantization via Layer-Wise Optimization Using Limited Training Data. 3329-3336 - Sheng-Wei Chen, Chun-Nan Chou, Edward Y. Chang:
EA-CG: An Approximate Second-Order Method for Training Fully-Connected Neural Networks. 3337-3346 - Shuo Chen, Chen Gong, Jian Yang, Ying Tai, Le Hui, Jun Li:
Data-Adaptive Metric Learning with Scale Alignment. 3347-3354 - Weijie Chen, Yuan Zhang, Di Xie, Shiliang Pu:
A Layer Decomposition-Recomposition Framework for Neuron Pruning towards Accurate Lightweight Networks. 3355-3362 - Xuelu Chen, Muhao Chen, Weijia Shi, Yizhou Sun, Carlo Zaniolo:
Embedding Uncertain Knowledge Graphs. 3363-3370 - Zitai Chen, Chuan Chen, Zibin Zheng, Yi Zhu:
Tensor Decomposition for Multilayer Networks Clustering. 3371-3378 - Zitian Chen, Yanwei Fu, Kaiyu Chen, Yu-Gang Jiang:
Image Block Augmentation for One-Shot Learning. 3379-3386 - Richard Cheng, Gábor Orosz, Richard M. Murray, Joel W. Burdick:
End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks. 3387-3395 - Daeyoung Choi, Wonjong Rhee:
Utilizing Class Information for Deep Network Representation Shaping. 3396-3403 - Andrew Cohen, Xingye Qiao, Lei Yu, Elliot Way, Xiangrong Tong:
Diverse Exploration via Conjugate Policies for Policy Gradient Methods. 3404-3411 - Eric Crawford, Joelle Pineau:
Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks. 3412-3420 - Giovanni Da San Martino, Alessandro Sperduti, Fabio Aiolli, Alessandro Moschitti:
Efficient Online Learning for Mapping Kernels on Linguistic Structures. 3421-3428 - Songmin Dai, Xiaoqiang Li, Lu Wang, Pin Wu, Weiqin Tong, Yimin Chen:
Learning Segmentation Masks with the Independence Prior. 3429-3436 - Sumanth Dathathri, Sicun Gao, Richard M. Murray:
Inverse Abstraction of Neural Networks Using Symbolic Interpolation. 3437-3444 - Maria Dimakopoulou, Zhengyuan Zhou, Susan Athey, Guido Imbens:
Balanced Linear Contextual Bandits. 3445-3453 - Lizhong Ding, Zhi Liu, Yu Li, Shizhong Liao, Yong Liu, Peng Yang, Ge Yu, Ling Shao, Xin Gao:
Linear Kernel Tests via Empirical Likelihood for High-Dimensional Data. 3454-3461 - Lizhong Ding, Yong Liu, Shizhong Liao, Yu Li, Peng Yang, Yijie Pan, Chao Huang, Ling Shao, Xin Gao:
Approximate Kernel Selection with Strong Approximate Consistency. 3462-3469 - Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
On-Line Adaptative Curriculum Learning for GANs. 3470-3477 - Bo Dong, Yang Gao, Swarup Chandra, Latifur Khan:
Multistream Classification with Relative Density Ratio Estimation. 3478-3485 - Qi Dong, Xiatian Zhu, Shaogang Gong:
Single-Label Multi-Class Image Classification by Deep Logistic Regression. 3486-3493 - Yonathan Efroni, Gal Dalal, Bruno Scherrer, Shie Mannor:
How to Combine Tree-Search Methods in Reinforcement Learning. 3494-3501 - Qing En, Lijuan Duan, Zhaoxiang Zhang, Xiang Bai, Yundong Zhang:
Human-Like Delicate Region Erasing Strategy for Weakly Supervised Detection. 3502-3509 - Lijie Fan, Wenbing Huang, Chuang Gan, Junzhou Huang, Boqing Gong:
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation. 3510-3517 - Jun-Peng Fang, Min-Ling Zhang:
Partial Multi-Label Learning via Credible Label Elicitation. 3518-3525 - Bahare Fatemi, Siamak Ravanbakhsh, David Poole:
Improved Knowledge Graph Embedding Using Background Taxonomic Information. 3526-3533 - Chao Feng, Chao Qian, Ke Tang:
Unsupervised Feature Selection by Pareto Optimization. 3534-3541 - Lei Feng, Bo An:
Partial Label Learning with Self-Guided Retraining. 3542-3549 - Lei Feng, Bo An, Shuo He:
Collaboration Based Multi-Label Learning. 3550-3557 - Yifan Feng, Haoxuan You, Zizhao Zhang, Rongrong Ji, Yue Gao:
Hypergraph Neural Networks. 3558-3565 - Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini:
Transductive Bounds for the Multi-Class Majority Vote Classifier. 3566-3573 - Stanislav Fort, Adam Scherlis:
The Goldilocks Zone: Towards Better Understanding of Neural Network Loss Landscapes. 3574-3581 - Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau:
Combined Reinforcement Learning via Abstract Representations. 3582-3589 - Yasuhiro Fujiwara, Sekitoshi Kanai, Junya Arai, Yasutoshi Ida, Naonori Ueda:
Efficient Data Point Pruning for One-Class SVM. 3590-3597 - Ryosuke Furuta, Naoto Inoue, Toshihiko Yamasaki:
Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing. 3598-3605 - Futoshi Futami, Zhenghang Cui, Issei Sato, Masashi Sugiyama:
Bayesian Posterior Approximation via Greedy Particle Optimization. 3606-3613 - Jinyang Gao, Junjie Yao, Yingxia Shao:
Towards Reliable Learning for High Stakes Applications. 3614-3621 - Jingyue Gao, Xiting Wang, Yasha Wang, Xing Xie:
Explainable Recommendation through Attentive Multi-View Learning. 3622-3629 - Tingran Gao, Shahab Asoodeh, Yi Huang, James Evans:
Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds. 3630-3637 - Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang:
Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting. 3638-3646 - Carles Gelada, Marc G. Bellemare:
Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift. 3647-3655 - Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang, Jieping Ye, Yan Liu:
Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting. 3656-3663 - AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang:
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees. 3664-3671 - Soheil Ghili, Ehsan Kazemi, Amin Karbasi:
Eliminating Latent Discrimination: Train Then Mask. 3672-3680 - Amirata Ghorbani, Abubakar Abid, James Y. Zou:
Interpretation of Neural Networks Is Fragile. 3681-3688 - Joachim Giesen, Sören Laue, Andreas Löhne, Christopher Schneider:
Using Benson's Algorithm for Regularization Parameter Tracking. 3689-3696 - Bin Gu, Zhouyuan Huo, Heng Huang:
Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy. 3697-3704 - Ning Gui, Danni Ge, Ziyin Hu:
AFS: An Attention-Based Mechanism for Supervised Feature Selection. 3705-3713 - Hongyu Guo, Yongyi Mao, Richong Zhang:
MixUp as Locally Linear Out-of-Manifold Regularization. 3714-3722 - Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tie-Yan Liu:
Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input. 3723-3730 - Tianyu Guo, Chang Xu, Boxin Shi, Chao Xu, Dacheng Tao:
Smooth Deep Image Generator from Noises. 3731-3738 - Xiaoxiao Guo, Shiyu Chang, Mo Yu, Gerald Tesauro, Murray Campbell:
Hybrid Reinforcement Learning with Expert State Sequences. 3739-3746 - Vivek Gupta, Rahul Wadbude, Nagarajan Natarajan, Harish Karnick, Prateek Jain, Piyush Rai:
Distributional Semantics Meets Multi-Label Learning. 3747-3754 - Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer:
Temporal Anomaly Detection: Calibrating the Surprise. 3755-3762 - Xiao He, Francesco Alesiani, Ammar Shaker:
Efficient and Scalable Multi-Task Regression on Massive Number of Tasks. 3763-3770 - Byeongho Heo, Minsik Lee, Sangdoo Yun, Jin Young Choi:
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary. 3771-3778 - Byeongho Heo, Minsik Lee, Sangdoo Yun, Jin Young Choi:
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons. 3779-3787 - Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik:
The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering. 3788-3795 - Matteo Hessel, Hubert Soyer, Lasse Espeholt, Wojciech Czarnecki, Simon Schmitt, Hado van Hasselt:
Multi-Task Deep Reinforcement Learning with PopArt. 3796-3803 - Fuxing Hong, Dongbo Huang, Ge Chen:
Interaction-Aware Factorization Machines for Recommender Systems. 3804-3811 - Hanzhang Hu, Debadeepta Dey, Martial Hebert, J. Andrew Bagnell:
Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing. 3812-3821 - Hao Hu, Liqiang Wang, Guo-Jun Qi:
Learning to Adaptively Scale Recurrent Neural Networks. 3822-3829 - Liang Hu, Songlei Jian, Longbing Cao, Zhiping Gu, Qingkui Chen, Artak Amirbekyan:
HERS: Modeling Influential Contexts with Heterogeneous Relations for Sparse and Cold-Start Recommendation. 3830-3837 - Menglei Hu, Songcan Chen:
One-Pass Incomplete Multi-View Clustering. 3838-3845 - Yi-Qi Hu, Yang Yu, Wei-Wei Tu, Qiang Yang, Yuqiang Chen, Wenyuan Dai:
Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion. 3846-3853 - Kun Huang, Bingbing Ni, Xiaokang Yang:
Efficient Quantization for Neural Networks with Binary Weights and Low Bitwidth Activations. 3854-3861 - Silu Huang, Chi Wang, Bolin Ding, Surajit Chaudhuri:
Efficient Identification of Approximate Best Configuration of Training in Large Datasets. 3862-3869 - Wenzhen Huang, Junge Zhang, Kaiqi Huang:
Bootstrap Estimated Uncertainty of the Environment Model for Model-Based Reinforcement Learning. 3870-3877 - Xiao Huang, Qingquan Song, Fan Yang, Xia Hu:
Large-Scale Heterogeneous Feature Embedding. 3878-3885 - Zhiwu Huang, Jiqing Wu, Luc Van Gool:
Manifold-Valued Image Generation with Wasserstein Generative Adversarial Nets. 3886-3893 - Le Hui, Xiang Li, Chen Gong, Meng Fang, Joey Tianyi Zhou, Jian Yang:
Inter-Class Angular Loss for Convolutional Neural Networks. 3894-3901 - Tsuyoshi Idé:
Tensorial Change Analysis Using Probabilistic Tensor Regression. 3902-3909 - Akira Imakura, Momo Matsuda, Xiucai Ye, Tetsuya Sakurai:
Complex Moment-Based Supervised Eigenmap for Dimensionality Reduction. 3910-3918 - Akane Iseki, Yusuke Mukuta, Yoshitaka Ushiku, Tatsuya Harada:
Estimating the Causal Effect from Partially Observed Time Series. 3919-3926 - Roxana Istrate, Florian Scheidegger, Giovanni Mariani, Dimitrios S. Nikolopoulos, Constantine Bekas, Adelmo Cristiano Innocenza Malossi:
TAPAS: Train-Less Accuracy Predictor for Architecture Search. 3927-3934 - Tomoharu Iwata, Hitoshi Shimizu:
Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data. 3935-3942 - Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, Martha White:
Meta-Descent for Online, Continual Prediction. 3943-3950 - Vinamra Jain, Prashant Doshi, Bikramjit Banerjee:
Model-Free IRL Using Maximum Likelihood Estimation. 3951-3958 - Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with Costly Features Using Deep Reinforcement Learning. 3959-3966 - Neal Jean, Sherrie Wang, Anshul Samar, George Azzari, David B. Lobell, Stefano Ermon:
Tile2Vec: Unsupervised Representation Learning for Spatially Distributed Data. 3967-3974 - Bin-Bin Jia, Min-Ling Zhang:
Multi-Dimensional Classification via kNN Feature Augmentation. 3975-3982 - Bingbing Jiang, Xingyu Wu, Kui Yu, Huanhuan Chen:
Joint Semi-Supervised Feature Selection and Classification through Bayesian Approach. 3983-3990 - Hansi Jiang, Haoyu Wang, Wenhao Hu, Deovrat Kakde, Arin Chaudhuri:
Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel. 3991-3998 - Heinrich Jiang:
Non-Asymptotic Uniform Rates of Consistency for k-NN Regression. 3999-4006 - Jiatao Jiang, Zhen Cui, Chunyan Xu, Jian Yang:
Gaussian-Induced Convolution for Graphs. 4007-4014 - Yue Jiang, Zhouhui Lian, Yingmin Tang, Jianguo Xiao:
SCFont: Structure-Guided Chinese Font Generation via Deep Stacked Networks. 4015-4022 - Binbin Jin, Hongke Zhao, Enhong Chen, Qi Liu, Yong Ge:
Estimating the Days to Success of Campaigns in Crowdfunding: A Deep Survival Perspective. 4023-4030 - Sunghwan Joo, Sungmin Cha, Taesup Moon:
DoPAMINE: Double-Sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling. 4031-4038 - Brendan Juba, Hai S. Le:
Precision-Recall versus Accuracy and the Role of Large Data Sets. 4039-4048 - Ata Kabán:
Dimension-Free Error Bounds from Random Projections. 4049-4056 - Zhao Kang, Yiwei Lu, Yuanzhang Su, Changsheng Li, Zenglin Xu:
Similarity Learning via Kernel Preserving Embedding. 4057-4064 - Rohit Keshari, Richa Singh, Mayank Vatsa:
Guided Dropout. 4065-4072 - Shun Kiyono, Jun Suzuki, Kentaro Inui:
Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework. 4073-4081 - Matthew Klawonn, Eric Heim, James A. Hendler:
Exploiting Class Learnability in Noisy Data. 4082-4089 - Quan Kong, Bin Tong, Martin Klinkigt, Yuki Watanabe, Naoto Akira, Tomokazu Murakami:
Active Generative Adversarial Network for Image Classification. 4090-4097 - Mark Kozdoba, Jakub Marecek, Tigran T. Tchrakian, Shie Mannor:
On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters. 4098-4105 - Atsutoshi Kumagai, Tomoharu Iwata:
Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations. 4106-4113 - Richard Kurle, Stephan Günnemann, Patrick van der Smagt:
Multi-Source Neural Variational Inference. 4114-4121 - Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama:
Unsupervised Domain Adaptation Based on Source-Guided Discrepancy. 4122-4129 - Yi-Yu Lai, Jennifer Neville, Dan Goldwasser:
TransConv: Relationship Embedding in Social Networks. 4130-4138 - Liang Lan, Yu Geng:
Accurate and Interpretable Factorization Machines. 4139-4146 - Jay Yoon Lee, Sanket Vaibhav Mehta, Michael L. Wick, Jean-Baptiste Tristan, Jaime G. Carbonell:
Gradient-Based Inference for Networks with Output Constraints. 4147-4154 - Kyubin Lee, Akshay Sood, Mark Craven:
Understanding Learned Models by Identifying Important Features at the Right Resolution. 4155-4163 - Sanghack Lee, Elias Bareinboim:
Structural Causal Bandits with Non-Manipulable Variables. 4164-4172 - Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin:
Communication-Efficient Stochastic Gradient MCMC for Neural Networks. 4173-4180 - Jia Li, Cong Fang, Zhouchen Lin:
Lifted Proximal Operator Machines. 4181-4188 - Jingjing Li, Mengmeng Jing, Ke Lu, Lei Zhu, Yang Yang, Zi Huang:
From Zero-Shot Learning to Cold-Start Recommendation. 4189-4196 - Linwei Li, Liangchen Guo, Zhenying He, Yinan Jing, X. Sean Wang:
X-DMM: Fast and Scalable Model Based Text Clustering. 4197-4204 - Ping Li:
Sign-Full Random Projections. 4205-4212 - Shihui Li, Yi Wu, Xinyue Cui, Honghua Dong, Fei Fang, Stuart Russell:
Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient. 4213-4220 - Xiang Li, Ben Kao, Zhaochun Ren, Dawei Yin:
Spectral Clustering in Heterogeneous Information Networks. 4221-4228 - Yanjun Li, Kai Zhang, Jun Wang, Sanjiv Kumar:
Learning Adaptive Random Features. 4229-4236 - Yufeng Li, Hai Wang, Tong Wei, Wei-Wei Tu:
Towards Automated Semi-Supervised Learning. 4237-4244 - Zejian Li, Yongchuan Tang, Wei Li, Yongxing He:
Learning Disentangled Representation with Pairwise Independence. 4245-4252 - Zheng Li, Ying Wei, Yu Zhang, Xiang Zhang, Xin Li:
Exploiting Coarse-to-Fine Task Transfer for Aspect-Level Sentiment Classification. 4253-4260 - Ziyao Li, Liang Zhang, Guojie Song:
SepNE: Bringing Separability to Network Embedding. 4261-4268 - Shangsong Liang:
Collaborative, Dynamic and Diversified User Profiling. 4269-4276 - Yitao Liang, Guy Van den Broeck:
Learning Logistic Circuits. 4277-4286 - Siyu Liao, Bo Yuan:
CircConv: A Structured Convolution with Low Complexity. 4287-4294 - Rung-Tzuo Liaw, Chuan-Kang Ting:
Evolutionary Manytasking Optimization Based on Symbiosis in Biocoenosis. 4295-4303 - Chen Lin, Xiaolin Shen, Si Chen, Muhua Zhu, Yanghua Xiao:
Non-Compensatory Psychological Models for Recommender Systems. 4304-4311 - Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin:
Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee. 4312-4319 - Zhenhua Lin, Hongtu Zhu:
MFPCA: Multiscale Functional Principal Component Analysis. 4320-4327 - Ao Liu, Zhibing Zhao, Chao Liao, Pinyan Lu, Lirong Xia:
Learning Plackett-Luce Mixtures from Partial Preferences. 4328-4335 - Ao Liu, Qiong Wu, Zhenming Liu, Lirong Xia:
Near-Neighbor Methods in Random Preference Completion. 4336-4343 - Dan Liu, Dawei Du, Libo Zhang, Tiejian Luo, Yanjun Wu, Feiyue Huang, Siwei Lyu:
Scale Invariant Fully Convolutional Network: Detecting Hands Efficiently. 4344-4351 - Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu:
Trust Region Evolution Strategies. 4352-4359 - Pengfei Liu, Jie Fu, Yue Dong, Xipeng Qiu, Jackie Chi Kit Cheung:
Learning Multi-Task Communication with Message Passing for Sequence Learning. 4360-4367 - Risheng Liu, Yuxi Zhang, Shichao Cheng, Xin Fan, Zhongxuan Luo:
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI. 4368-4375 - Rui Liu, Tianyi Wu, Barzan Mozafari:
A Bandit Approach to Maximum Inner Product Search. 4376-4383 - Vincent Liu, Raksha Kumaraswamy, Lei Le, Martha White:
The Utility of Sparse Representations for Control in Reinforcement Learning. 4384-4391 - Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Chang Tang, En Zhu, Jianping Yin, Wen Gao:
Efficient and Effective Incomplete Multi-View Clustering. 4392-4399 - Xuanwu Liu, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Yazhou Ren, Maozu Guo:
Ranking-Based Deep Cross-Modal Hashing. 4400-4407 - Yanbin Liu, Yan Yan, Ling Chen, Yahong Han, Yi Yang:
Adaptive Sparse Confidence-Weighted Learning for Online Feature Selection. 4408-4415 - Zhao-Yang Liu, Sheng-Jun Huang:
Active Sampling for Open-Set Classification without Initial Annotation. 4416-4423 - Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi:
GeniePath: Graph Neural Networks with Adaptive Receptive Paths. 4424-4431 - Guansong Lu, Zhiming Zhou, Yuxuan Song, Kan Ren, Yong Yu:
Guiding the One-to-One Mapping in CycleGAN via Optimal Transport. 4432-4439 - Yao Lu, Guangming Lu, Bob Zhang, Yuanrong Xu, Jinxing Li:
Super Sparse Convolutional Neural Networks. 4440-4447 - You Lu, Zhiyuan Liu, Bert Huang:
Block Belief Propagation for Parameter Learning in Markov Random Fields. 4448-4455 - Yuanfu Lu, Chuan Shi, Linmei Hu, Zhiyuan Liu:
Relation Structure-Aware Heterogeneous Information Network Embedding. 4456-4463 - Chen Luo, Anshumali Shrivastava:
Scaling-Up Split-Merge MCMC with Locality Sensitive Sampling (LSS). 4464-4471 - Lei Luo, Jie Xu, Cheng Deng, Heng Huang:
Orthogonality-Promoting Dictionary Learning via Bayesian Inference. 4472-4479 - Lei Luo, Jie Xu, Cheng Deng, Heng Huang:
Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees. 4480-4487 - Simon Luo, Mahito Sugiyama:
Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions. 4488-4495 - Siqiang Luo:
Distributed PageRank Computation: An Improved Theoretical Study. 4496-4503 - Clare Lyle, Marc G. Bellemare, Pablo Samuel Castro:
A Comparative Analysis of Expected and Distributional Reinforcement Learning. 4504-4511 - Shuai Ma, Jia Yuan Yu:
State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning. 4512-4519 - Yuchao Ma, Hassan Ghasemzadeh:
LabelForest: Non-Parametric Semi-Supervised Learning for Activity Recognition. 4520-4527 - Kehelwala Dewage Gayan Maduranga, Kyle E. Helfrich, Qiang Ye:
Complex Unitary Recurrent Neural Networks Using Scaled Cayley Transform. 4528-4535 - Saeed Mahloujifar, Dimitrios I. Diochnos, Mohammad Mahmoody:
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure. 4536-4543 - Maggie Makar, Adith Swaminathan, Emre Kiciman:
A Distillation Approach to Data Efficient Individual Treatment Effect Estimation. 4544-4551 - André Gustavo Maletzke, Denis Moreira dos Reis, Everton Alvares Cherman, Gustavo E. A. P. A. Batista:
DyS: A Framework for Mixture Models in Quantification. 4552-4560 - Raghuram Mandyam Annasamy, Katia P. Sycara:
Towards Better Interpretability in Deep Q-Networks. 4561-4569 - Ryan McBride, Ke Wang, Zhouyang Ren, Wenyuan Li:
Cost-Sensitive Learning to Rank. 4570-4577 - Shaobo Min, Xuejin Chen, Zheng-Jun Zha, Feng Wu, Yongdong Zhang:
A Two-Stream Mutual Attention Network for Semi-Supervised Biomedical Segmentation with Noisy Labels. 4578-4585 - Di Ming, Chris Ding, Feiping Nie:
A Probabilistic Derivation of LASSO and L12-Norm Feature Selections. 4586-4593 - Kohei Miyaguchi, Hiroshi Kajino:
Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting. 4594-4601 - Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, Martin Grohe:
Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks. 4602-4609 - Sudipto Mukherjee, Himanshu Asnani, Eugene Lin, Sreeram Kannan:
ClusterGAN: Latent Space Clustering in Generative Adversarial Networks. 4610-4617 - So Nakashima, Takanori Maehara:
Subspace Selection via DR-Submodular Maximization on Lattices. 4618-4625 - Hyoungwook Nam, Segwang Kim, Kyomin Jung:
Number Sequence Prediction Problems for Evaluating Computational Powers of Neural Networks. 4626-4633 - Yusuke Narita, Shota Yasui, Kohei Yata:
Efficient Counterfactual Learning from Bandit Feedback. 4634-4641 - Pablo Navarrete Michelini, Hanwen Liu, Dan Zhu:
Multigrid Backprojection Super-Resolution and Deep Filter Visualization. 4642-4650 - Alexander G. Ororbia II, Ankur Arjun Mali:
Biologically Motivated Algorithms for Propagating Local Target Representations. 4651-4658 - Takayuki Osogami, Rudy Raymond:
Determinantal Reinforcement Learning. 4659-4666 - Dipan K. Pal, Marios Savvides:
Non-Parametric Transformation Networks for Learning General Invariances from Data. 4667-4674 - Feiyang Pan, Qingpeng Cai, Anxiang Zeng, Chun-Xiang Pan, Qing Da, Hua-Lin He, Qing He, Pingzhong Tang:
Policy Optimization with Model-Based Explorations. 4675-4682 - Yu Pan, Jing Xu, Maolin Wang, Jinmian Ye, Fei Wang, Kun Bai, Zenglin Xu:
Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition. 4683-4690 - Zhen-Jia Pang, Ruo-Ze Liu, Zhou-Yu Meng, Yi Zhang, Yang Yu, Tong Lu:
On Reinforcement Learning for Full-Length Game of StarCraft. 4691-4698 - Sungrae Park, Kyungwoo Song, Mingi Ji, Wonsung Lee, Il-Chul Moon:
Adversarial Dropout for Recurrent Neural Networks. 4699-4706 - Minlong Peng, Qi Zhang, Xiaoyu Xing, Tao Gui, Xuanjing Huang, Yu-Gang Jiang, Keyu Ding, Zhigang Chen:
Trainable Undersampling for Class-Imbalance Learning. 4707-4714 - María Pérez-Ortiz, Peter Tiño, Rafal Mantiuk, César Hervás-Martínez:
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets. 4715-4722 - Mirko Polato, Fabio Aiolli:
Interpretable Preference Learning: A Game Theoretic Framework for Large Margin On-Line Feature and Rule Learning. 4723-4730 - Marcelo O. R. Prates, Pedro H. C. Avelar, Henrique Lemos, Luís C. Lamb, Moshe Y. Vardi:
Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP. 4731-4738 - Qi Qian, Shenghuo Zhu, Jiasheng Tang, Rong Jin, Baigui Sun, Hao Li:
Robust Optimization over Multiple Domains. 4739-4746 - You Qiaoben, Zheng Wang, Jianguo Li, Yinpeng Dong, Yu-Gang Jiang, Jun Zhu:
Composite Binary Decomposition Networks. 4747-4754 - Xiaoyu Qin, Kai Ming Ting, Ye Zhu, Vincent C. S. Lee:
Nearest-Neighbour-Induced Isolation Similarity and Its Impact on Density-Based Clustering. 4755-4762 - Alexander Ratner, Braden Hancock, Jared Dunnmon, Frederic Sala, Shreyash Pandey, Christopher Ré:
Training Complex Models with Multi-Task Weak Supervision. 4763-4771 - Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh:
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence. 4772-4779 - Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V. Le:
Regularized Evolution for Image Classifier Architecture Search. 4780-4789 - Ievgen Redko, Charlotte Laclau:
On Fair Cost Sharing Games in Machine Learning. 4790-4797 - Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Weinan Zhang, Lin Qiu, Yong Yu:
Deep Recurrent Survival Analysis. 4798-4805 - Pengjie Ren, Zhumin Chen, Jing Li, Zhaochun Ren, Jun Ma, Maarten de Rijke:
RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-Based Recommendation. 4806-4813 - Tao Ruan, Ting Liu, Zilong Huang, Yunchao Wei, Shikui Wei, Yao Zhao:
Devil in the Details: Towards Accurate Single and Multiple Human Parsing. 4814-4821 - Sebastian Ruder, Joachim Bingel, Isabelle Augenstein, Anders Søgaard:
Latent Multi-Task Architecture Learning. 4822-4829 - Aadirupa Saha, Rakesh Shivanna, Chiranjib Bhattacharyya:
How Many Pairwise Preferences Do We Need to Rank a Graph Consistently? 4830-4837 - Tomoya Sakai, Nobuyuki Shimizu:
Covariate Shift Adaptation on Learning from Positive and Unlabeled Data. 4838-4845 - Patrick Schwab, Djordje Miladinovic, Walter Karlen:
Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks. 4846-4853 - Arik Senderovich, J. Christopher Beck, Avigdor Gal, Matthias Weidlich:
Congestion Graphs for Automated Time Predictions. 4854-4861 - Kristen A. Severson, Soumya Ghosh, Kenney Ng:
Unsupervised Learning with Contrastive Latent Variable Models. 4862-4869 - Kulin Shah, Naresh Manwani:
Sparse Reject Option Classifier Using Successive Linear Programming. 4870-4877 - Jin Shang, Mingxuan Sun:
Geometric Hawkes Processes with Graph Convolutional Recurrent Neural Networks. 4878-4885 - Zhiqiang Shen, Zhankui He, Xiangyang Xue:
MEAL: Multi-Model Ensemble via Adversarial Learning. 4886-4893 - Xiang-Rong Sheng, De-Chuan Zhan, Su Lu, Yuan Jiang:
Multi-View Anomaly Detection: Neighborhood in Locality Matters. 4894-4901 - Jing-Cheng Shi, Yang Yu, Qing Da, Shi-Yong Chen, Anxiang Zeng:
Virtual-Taobao: Virtualizing Real-World Online Retail Environment for Reinforcement Learning. 4902-4909 - Shu-Ting Shi, Ming Li, David Lo, Ferdian Thung, Xuan Huo:
Automatic Code Review by Learning the Revision of Source Code. 4910-4917 - Xiaofei Shi, David P. Woodruff:
Sublinear Time Numerical Linear Algebra for Structured Matrices. 4918-4925 - Yaxin Shi, Donna Xu, Yuangang Pan, Ivor W. Tsang, Shirui Pan:
Label Embedding with Partial Heterogeneous Contexts. 4926-4933 - David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer, David S. Rosenblum:
Evaluating Recommender System Stability with Influence-Guided Fuzzing. 4934-4942 - Hai Shu, Hongtu Zhu:
Sensitivity Analysis of Deep Neural Networks. 4943-4950 - Yang Shu, Zhangjie Cao, Mingsheng Long, Jianmin Wang:
Transferable Curriculum for Weakly-Supervised Domain Adaptation. 4951-4958 - Aditya Siddhant, Anuj Kumar Goyal, Angeliki Metallinou:
Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents. 4959-4966 - Thiago D. Simão, Matthijs T. J. Spaan:
Safe Policy Improvement with Baseline Bootstrapping in Factored Environments. 4967-4974 - Christopher L. Simpkins, Charles L. Isbell Jr.:
Composable Modular Reinforcement Learning. 4975-4982 - Kyungwoo Song, Mingi Ji, Sungrae Park, Il-Chul Moon:
Hierarchical Context Enabled Recurrent Neural Network for Recommendation. 4983-4991 - Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Mai Xu:
Diversity-Driven Extensible Hierarchical Reinforcement Learning. 4992-4999 - Amber Srivastava, Mayank Baranwal, Srinivasa M. Salapaka:
On the Persistence of Clustering Solutions and True Number of Clusters in a Dataset. 5000-5007 - Kai Su, Xin Geng:
Soft Facial Landmark Detection by Label Distribution Learning. 5008-5015 - Lijuan Sun, Songhe Feng, Tao Wang, Congyan Lang, Yi Jin:
Partial Multi-Label Learning by Low-Rank and Sparse Decomposition. 5016-5023 - Qigong Sun, Fanhua Shang, Kang Yang, Xiufang Li, Yan Ren, Licheng Jiao:
Multi-Precision Quantized Neural Networks via Encoding Decomposition of {-1, +1}. 5024-5032 - Tao Sun, Penghang Yin, Dongsheng Li, Chun Huang, Lei Guan, Hao Jiang:
Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms. 5033-5040 - Xin Sun, Zenghui Song, Junyu Dong, Yongbo Yu, Claudia Plant, Christian Böhm:
Network Structure and Transfer Behaviors Embedding via Deep Prediction Model. 5041-5048 - Yi Sun, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
Learning Vine Copula Models for Synthetic Data Generation. 5049-5057 - Fariborz Taherkhani, Hadi Kazemi, Nasser M. Nasrabadi:
Matrix Completion for Graph-Based Deep Semi-Supervised Learning. 5058-5065 - Hiroshi Takahashi, Tomoharu Iwata, Yuki Yamanaka, Masanori Yamada, Satoshi Yagi:
Variational Autoencoder with Implicit Optimal Priors. 5066-5073 - Sho Takase, Jun Suzuki, Masaaki Nagata:
Character n-Gram Embeddings to Improve RNN Language Models. 5074-5082 - Zhi-Hao Tan, Teng Zhang, Wei Wang:
Coreset Stochastic Variance-Reduced Gradient with Application to Optimal Margin Distribution Machine. 5083-5090 - Yusuke Tanaka, Tomoharu Iwata, Toshiyuki Tanaka, Takeshi Kurashima, Maya Okawa, Hiroyuki Toda:
Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities. 5091-5099 - Chang Tang, Xinzhong Zhu, Xinwang Liu, Lizhe Wang:
Cross-View Local Structure Preserved Diversity and Consensus Learning for Multi-View Unsupervised Feature Selection. 5101-5108 - Shijie Tang, Yuan Yao, Suwei Zhang, Feng Xu, Tianxiao Gu, Hanghang Tong, Xiaohui Yan, Jian Lu:
An Integral Tag Recommendation Model for Textual Content. 5109-5116 - Ying-Peng Tang, Sheng-Jun Huang:
Self-Paced Active Learning: Query the Right Thing at the Right Time. 5117-5124 - Hanqing Tao, Shiwei Tong, Hongke Zhao, Tong Xu, Binbin Jin, Qi Liu:
A Radical-Aware Attention-Based Model for Chinese Text Classification. 5125-5132 - (Withdrawn) Optimization of Hierarchical Regression Model with Application to Optimizing Multi-Response Regression K-ary Trees. 5133-5142
- Yi Tay, Shuai Zhang, Anh Tuan Luu, Siu Cheung Hui, Lina Yao, Tran Dang Quang Vinh:
Holographic Factorization Machines for Recommendation. 5143-5150 - Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama:
Clipped Matrix Completion: A Remedy for Ceiling Effects. 5151-5158 - Erik Thiel, Morteza Haghir Chehreghani, Devdatt P. Dubhashi:
A Non-Convex Optimization Approach to Correlation Clustering. 5159-5166 - Kai Tian, Shuigeng Zhou, Jianping Fan, Jihong Guan:
Learning Competitive and Discriminative Reconstructions for Anomaly Detection. 5167-5174 - Saket Tiwari, Philip S. Thomas:
Natural Option Critic. 5175-5182 - Christopher Tran, Elena Zheleva:
Learning Triggers for Heterogeneous Treatment Effects. 5183-5190 - Ngoc-Trung Tran, Tuan-Anh Bui, Ngai-Man Cheung:
Improving GAN with Neighbors Embedding and Gradient Matching. 5191-5198 - Amin Vahedian, Xun Zhou, Ling Tong, W. Nick Street, Yanhua Li:
Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data. 5199-5206 - Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera:
Automatic Bayesian Density Analysis. 5207-5215 - Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung:
Robust Anomaly Detection in Videos Using Multilevel Representations. 5216-5223 - Chengwei Wang, Tengfei Zhou, Chen Chen, Tianlei Hu, Gang Chen:
CAMO: A Collaborative Ranking Method for Content Based Recommendation. 5224-5231 - Chuan Wang, Haibin Huang, Xiaoguang Han, Jue Wang:
Video Inpainting by Jointly Learning Temporal Structure and Spatial Details. 5232-5239 - Hanmo Wang, Runwu Zhou, Yi-Dong Shen:
Bounding Uncertainty for Active Batch Selection. 5240-5247 - Haoyu Wang, Nan Shao, Defu Lian:
Adversarial Binary Collaborative Filtering for Implicit Feedback. 5248-5255 - Jing Wang, Xin Geng:
Theoretical Analysis of Label Distribution Learning. 5256-5263 - Jing Wang, Atsushi Suzuki, Linchuan Xu, Feng Tian, Liang Yang, Kenji Yamanishi:
Orderly Subspace Clustering. 5264-5272 - Jingyuan Wang, Kai Feng, Junjie Wu:
SVM-Based Deep Stacking Networks. 5273-5280 - Lichen Wang, Jiaxiang Wu, Shao-Lun Huang, Lizhong Zheng, Xiangxiang Xu, Lin Zhang, Junzhou Huang:
An Efficient Approach to Informative Feature Extraction from Multimodal Data. 5281-5288 - Shaoqi Wang, Aidi Pi, Xiaobo Zhou:
Scalable Distributed DL Training: Batching Communication and Computation. 5289-5296