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ORCIDBigData Conference 2020: Atlanta, GA, USA
- Xintao Wu, Chris Jermaine, Li Xiong, Xiaohua Hu, Olivera Kotevska, Siyuan Lu, Weija Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz:
2020 IEEE International Conference on Big Data (IEEE BigData 2020), Atlanta, GA, USA, December 10-13, 2020. IEEE 2020, ISBN 978-1-7281-6251-5 - Jeannette M. Wing:
Data for Good: Ensuring the Responsible Use of Data to Benefit Society. 1-2 - Ozgun Pinarer, Sultan Turhan:
Pandemic Effect: Degradation of Speech Reception Due to Medical Masks. 1-7 - Alan B. Cannaday, Curt H. Davis, Andrew J. Maltenfort:
Evaluation of Fuzzy Integral Data Fusion Methods for Rare Object Detection in High-Resolution Satellite Imagery. 1-10 - John N. Celona, Louis Halamek, Adam Seiver:
Making "Magic" with Engineered Decisions, Data, and Processes: A Hospital Operations Center. 1-8 - A. K. Singh, Navneet Goyal:
Understanding and Mitigating Threats from Android Hybrid Apps Using Machine Learning. 1-9 - Divesh Srivastava:
Towards High-Quality Big Data: Lessons from FIT. 4 - Sara Ahmadian, Shahrzad Haddadan:
A theoretical analysis of graph evolution caused by triadic closure and algorithmic implications. 5-14 - Yujing Chen, Yue Ning, Martin Slawski, Huzefa Rangwala:
Asynchronous Online Federated Learning for Edge Devices with Non-IID Data. 15-24 - Jie Ding, Bangjun Ding:
"To Tell You the Truth" by Interval-Private Data. 25-32 - Alexander Geiger, Dongyu Liu
, Sarah Alnegheimish, Alfredo Cuesta-Infante, Kalyan Veeramachaneni:
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks. 33-43 - Sheng Guan, Peng Lin, Hanchao Ma, Yinghui Wu:
GEDet: Adversarially Learned Few-shot Detection of Erroneous Nodes in Graphs. 44-53 - Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal:
Augmenting Deep Learning with Relational Knowledge from Markov Logic Networks. 54-63 - Farzaneh Khoshnevisan, Min Chi:
An Adversarial Domain Separation Framework for Septic Shock Early Prediction Across EHR Systems. 64-73 - Minkyu Kim, Suan Lee, Jinho Kim:
Combining Multiple Implicit-Explicit Interactions for Regression Analysis. 74-83 - Peter Sanders:
Connecting MapReduce Computations to Realistic Machine Models. 84-93 - Noah Schwalb, Edward Schwalb:
Applications of Particle Swarm Optimization to System Identification and Supervised Learning. 94-101 - Vinícius M. A. de Souza, Farhan Asif Chowdhury, Abdullah Mueen:
Unsupervised Drift Detection on High-speed Data Streams. 102-111 - Samarth Tripathi, Jiayi Liu, Sauptik Dhar, Unmesh Kurup, Mohak Shah:
Improving Model Training by Periodic Sampling over Weight Distributions. 112-122 - Ziyao Zhang, Liang Ma, Kin K. Leung, Konstantinos Poularakis, Mudhakar Srivatsa:
State Action Separable Reinforcement Learning. 123-132 - Jerry Chee, Ping Li:
Understanding and Detecting Convergence for Stochastic Gradient Descent with Momentum. 133-140 - Cheng Chen, Junjie Yang, Yi Zhou:
Neural Network Training Techniques Regularize Optimization Trajectory: An Empirical Study. 141-146 - Walter Gerych, Luke Buquicchio, Kavin Chandrasekaran, Abdulaziz Alajaji, Hamid Mansoor, Aidan Murphy, Elke A. Rundensteiner, Emmanuel Agu:
BurstPU: Classification of Weakly Labeled Datasets with Sequential Bias. 147-154 - Mohammad J. Hashemi, Eric Keller:
General Domain Adaptation Through Proportional Progressive Pseudo Labeling. 155-162 - Huan He, Yuanzhe Xi, Joyce C. Ho:
Fast and Accurate Tensor Decomposition without a High Performance Computing Machine. 163-170 - Mohammad Rasool Izadi, Yihao Fang, Robert Stevenson, Lizhen Lin:
Optimization of Graph Neural Networks with Natural Gradient Descent. 171-179 - Zhaoxi Li, Jun He, Hongyan Liu, Xiaoyong Du:
Combining Global and Sequential Patterns for Multivariate Time Series Forecasting. 180-187 - Matthew Middlehurst, James Large, Anthony J. Bagnall:
The Canonical Interval Forest (CIF) Classifier for Time Series Classification. 188-195 - Gyoung S. Na, Hyun Woo Kim, Hyunju Chang:
Scale-Aware Graph-Based Machine Learning for Accurate Molecular Property Prediction. 196-203 - Yang Ni, David Jones, Zeya Wang:
Consensus Variational and Monte Carlo Algorithms for Bayesian Nonparametric Clustering. 204-209 - Edward Schwalb:
Sketches: Fast Membership Scans for Continuous Variable Predicate Workloads. 210-217 - Taruna Seth, Vipin Chaudhary:
A Predictive Analytics Framework for Insider Trading Events. 218-225 - Chengbin Sun, Hailong Sun, Xudong Liu:
Robust Adversarial Active Learning with a Novel Diversity Constraint. 226-231 - Qiyao Wang, Haiyan Wang, Chetan Gupta, Aniruddha Rajendra Rao, Hamed Khorasgani:
A Non-linear Function-on-Function Model for Regression with Time Series Data. 232-239 - Tianyang Xie, Jie Ding:
Forecasting with Multiple Seasonality. 240-245 - Kevin Bruhwiler, Paahuni Khandelwal, Daniel Rammer, Samuel Armstrong, Sangmi Lee Pallickara, Shrideep Pallickara:
Lightweight, Embeddings Based Storage and Model Construction Over Satellite Data Collections. 246-255 - Hariharan Devarajan, Anthony Kougkas, Xian-He Sun:
HReplica: A Dynamic Data Replication Engine with Adaptive Compression for Multi-Tiered Storage. 256-265 - Ayat Fekry, Lucian Carata, Thomas F. J.-M. Pasquier, Andrew Rice:
Accelerating the Configuration Tuning of Big Data Analytics with Similarity-aware Multitask Bayesian Optimization. 266-275 - Markus Götz, Charlotte Debus, Daniel Coquelin, Kai Krajsek, Claudia Comito, Philipp Knechtges, Björn Hagemeier, Michael Tarnawa, Simon Hanselmann, Martin Siggel, Achim Basermann, Achim Streit:
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics. 276-287 - Vipul Gupta, Swanand Kadhe, Thomas A. Courtade, Michael W. Mahoney, Kannan Ramchandran:
OverSketched Newton: Fast Convex Optimization for Serverless Systems. 288-297 - Mark Hamilton, Nick Gonsalves, Christina Lee, Anand Raman, Brendan Walsh, Siddhartha Prasad, Dalitso Banda, Lucy Zhang, Lei Zhang, William T. Freeman:
Large-Scale Intelligent Microservices. 298-309 - Chris Liu, Pengfei Zhang, Bo Tang, Hang Shen, Ziliang Lai, Eric Lo, Korris Fu-Lai Chung:
Towards Self-Tuning Parameter Servers. 310-319 - Matthew Madany, Kyle Marcus, Steven Peltier, Mark H. Ellisman, Ilkay Altintas:
NeuroKube: An Automated and Autoscaling Neuroimaging Reconstruction Framework using Cloud Native Computing and A.I. 320-330 - Michael J. Mior, Kenneth Salem:
ReSpark: Automatic Caching for Iterative Applications in Apache Spark. 331-340 - Frank Pallas, Dimitri Staufer, Jörn Kuhlenkamp:
Evaluating the Accuracy of Cloud NLP Services Using Ground-Truth Experiments. 341-350 - Martin Perdacher, Claudia Plant, Christian Böhm:
Improved Data Locality Using Morton-order Curve on the Example of LU Decomposition. 351-360 - Buvaneswari Ramanan, Lawrence M. Drabeck, Thomas Woo, Troy Cauble, Anil Rana:
~PB&J~ - Easy Automation of Data Science/Machine Learning Workflows. 361-371 - Paula Ta-Shma, Guy Khazma, Gal Lushi, Oshrit Feder:
Extensible Data Skipping. 372-382 - Tanuj Kr Aasawat, Tahsin Reza, Kazuki Yoshizoe, Matei Ripeanu:
HyGN: Hybrid Graph Engine for NUMA. 383-390 - Vitor Pinheiro de Almeida, Sukanya Bhowmik, Guilherme F. Lima, Markus Endler, Kurt Rothermel:
DSCEP: An Infrastructure for Decentralized Semantic Complex Event Processing. 391-398 - Sikder Tahsin Al-Amin, Siva Uday Sampreeth Chebolu, Carlos Ordonez:
Extending the R Language with a Scalable Matrix Summarization Operator. 399-405 - Soumia Benkrid, Yacine Mestoui, Ladjel Bellatreche, Carlos Ordonez:
A Genetic Optimization Physical Planner for Big Data Warehouses. 406-412 - Christian Böhm, Claudia Plant:
Massively Parallel Random Number Generation. 413-419 - Yi-Long Chen, Pangfeng Liu, Jan-Jan Wu:
An Adaptive Layer Expansion Algorithm for Efficient Training of Deep Neural Networks. 420-425 - Ryan D. Friese, Burcu Ozcelik Mutlu, Nathan R. Tallent, Joshua Suetterlein, Jan Strube:
Effectively Using Remote I/O For Work Composition in Distributed Workflows. 426-433 - Morgan K. Geldenhuys, Lauritz Thamsen, Odej Kao:
Chiron: Optimizing Fault Tolerance in QoS-aware Distributed Stream Processing Jobs. 434-440 - James Henrydoss, Steve Cruz, Chunchun Li, Manuel Günther, Terrance E. Boult:
Enhancing Open-Set Recognition using Clustering-based Extreme Value Machine (C-EVM). 441-448 - Hirokuni Kitahara, Kugamoorthy Gajananan, Yuji Watanabe:
Highly-Scalable Container Integrity Monitoring for Large-Scale Kubernetes Cluster. 449-454 - Qizhong Mao, Mohiuddin Abdul Qader, Vagelis Hristidis:
Comprehensive Comparison of LSM Architectures for Spatial Data. 455-460 - Abbas Mazloumi, Chengshuo Xu, Zhijia Zhao, Rajiv Gupta:
BEAD: Batched Evaluation of Iterative Graph Queries with Evolving Analytics Demands. 461-468 - Md Hasanuzzaman Noor, Leonidas Fegaras:
Translation of Array-Based Loops to Spark SQL. 469-476 - Wei Rang, Donglin Yang, Dazhao Cheng:
A Shared Memory Cache Layer across Multiple Executors in Apache Spark. 477-482 - Alessio Bernardo, Heitor Murilo Gomes, Jacob Montiel, Bernhard Pfahringer, Albert Bifet, Emanuele Della Valle:
C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams. 483-492 - Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Ruizhe Ma, Rafal A. Angryk:
On the Mining of the Minimal Set of Time Series Data Shapelets. 493-502 - Xiaoyu Ge, Xiaozhong Zhang, Panos K. Chrysanthis:
ExNav: An Interactive Big Data Exploration Framework for Big Unstructured Data. 503-512 - Himanshu Gupta, Rajmohan C, Sameep Mehta, Kiran Pulapa:
On Efficiently Processing Business Lineage Queries. 513-522 - Dimitrios Karapiperis, Aris Gkoulalas-Divanis, Vassilios S. Verykios:
Efficient Record Linkage in Data Streams. 523-532 - Iouliana Litou, Vana Kalogeraki:
Cost-Aware Influence Maximization in Multi-Attribute Networks. 533-542 - Jiamin Lu, Cheng Yang, Bingfa Wang, Jun Feng:
FP-ExtVP: Accelerating Distributed SPARQL queries by Exploiting Load-adaptive Partitioning. 543-550 - Shaina Raza, Chen Ding:
A Regularized Model to Trade-off between Accuracy and Diversity in a News Recommender System. 551-560 - Kenneth Teo Tian Shun, Eko Edita Limanta, Arijit Khan:
An Evaluation of Backpropagation Interpretability for Graph Classification with Deep Learning. 561-570 - Samriddhi Singla, Ahmed Eldawy:
Raptor Zonal Statistics: Fully Distributed Zonal Statistics of Big Raster + Vector Data. 571-580 - Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney:
PyHessian: Neural Networks Through the Lens of the Hessian. 581-590 - Amanuel Alambo, Cori Lohstroh, Erik Madaus, Swati Padhee, Brandy Foster, Tanvi Banerjee, Krishnaprasad Thirunarayan, Michael L. Raymer:
Topic-Centric Unsupervised Multi-Document Summarization of Scientific and News Articles. 591-596 - Maroua Bahri, Bruno Veloso, Albert Bifet, João Gama:
AutoML for Stream k-Nearest Neighbors Classification. 597-602 - Sambaran Bandyopadhyay, Manasvi Aggarwal, M. Narasimha Murty:
Self-supervised Hierarchical Graph Neural Network for Graph Representation. 603-608 - Christian Böhm, Claudia Plant:
Massively Parallel Graph Drawing and Representation Learning. 609-616 - Du Chen, Yuming Deng, Guangrui Ma, Hao Ge, Yunwei Qi, Ying Rong, Xun Zhang, Huan Zheng:
Inventory Based Recommendation Algorithms. 617-622 - Sidan Gao, Nodirbek Korchiev, Vodelina Samatova, Kemafor Anyanwu:
Efficient Constrained Subgraph Extraction for Exploratory Discovery in Large Knowledge Graphs. 623-630 - Ziyi Kou, Daniel Yue Zhang, Lanyu Shang, Dong Wang:
ExFaux: A Weakly Supervised Approach to Explainable Fauxtography Detection. 631-636 - Lukas Probst, Heiko Schuldt, Philipp Seidenschwarz, Martin Rumo:
StreamTeam-Football: Analyzing Football Matches in Real-Time on the Basis of Position Streams. 637-644 - Hadi Salman, Justin Zhan:
Semi-Supervised Learning and Feature Fusion for Multi-view Data Clustering. 645-650 - Sabarish Vadarevu, Vijay Karamcheti:
A new heuristic algorithm for fast k-segmentation. 651-658 - Ran Bai, Ziliang Lai, Eric Lo, Wing-Kai Hon, Pengfei Zhang:
Practical Range Counting over Data Streams. 659-668 - Sambaran Bandyopadhyay, Kishalay Das, M. Narasimha Murty:
Hypergraph Attention Isomorphism Network by Learning Line Graph Expansion. 669-678 - Aarzoo Dhiman, Durga Toshniwal:
An Unsupervised Misinformation Detection Framework to Analyze the Users using COVID-19 Twitter Data. 679-688 - Ahnaf Farhan, Mahmud Shahriar Hossain:
VizObj2Vec: Contextual Representation Learning for Visual Objects in Video-frames. 689-698 - Umar Farooq, A. B. Siddique, Fuad T. Jamour, Zhijia Zhao, Vagelis Hristidis:
App-Aware Response Synthesis for User Reviews. 699-708 - Yizhan Xu, Sungwon Han, Sungwon Park, Meeyoung Cha, Cheng-Te Li:
A Comprehensive and Adversarial Approach to Self-Supervised Representation Learning. 709-717 - Sunwoo Lee, Qiao Kang, Ankit Agrawal, Alok N. Choudhary, Wei-keng Liao:
Communication-Efficient Local Stochastic Gradient Descent for Scalable Deep Learning. 718-727 - Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen Guo, Kannan Achan, Philip S. Yu:
Basket Recommendation with Multi-Intent Translation Graph Neural Network. 728-737 - Fangbing Liu, Qing Wang:
Dynamic Chunkwise CNN for Distantly Supervised Relation Extraction. 738-747 - Nicholas Micallef, Bing He, Srijan Kumar, Mustaque Ahamad, Nasir D. Memon:
The Role of the Crowd in Countering Misinformation: A Case Study of the COVID-19 Infodemic. 748-757 - Xiao Qin, Cao Xiao, Tengfei Ma, Tabassum Kakar, Susmitha Wunnava, Xiangnan Kong, Elke A. Rundensteiner, Fei Wang:
Supervised Topic Compositional Neural Language Model for Clinical Narrative Understanding. 758-767 - Nikitha Rao, Chetan Bansal, Thomas Zimmermann, Ahmed Hassan Awadallah, Nachiappan Nagappan:
Analyzing Web Search Behavior for Software Engineering Tasks. 768-777 - Alexander Rodríguez, Bijaya Adhikari, Andrés D. González, Charles D. Nicholson, Anil Vullikanti, B. Aditya Prakash:
Mapping Network States using Connectivity Queries. 778-787 - Ehsan Sadrfaridpour, Korey Palmer, Ilya Safro:
AML-SVM: Adaptive Multilevel Learning with Support Vector Machines. 788-797 - Qiuling Suo, Weida Zhong, Guangxu Xun, Jianhui Sun, Changyou Chen, Aidong Zhang:
GLIMA: Global and Local Time Series Imputation with Multi-directional Attention Learning. 798-807 - Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner:
Learning Similarity-Preserving Meta-Embedding for Text Mining. 808-817 - Xuan Wang, Yingjun Guan, Yu Zhang, Qi Li, Jiawei Han:
Pattern-enhanced Named Entity Recognition with Distant Supervision. 818-827 - Xuan Wang, Yu Zhang, Aabhas Chauhan, Qi Li, Jiawei Han:
Textual Evidence Mining via Spherical Heterogeneous Information Network Embedding. 828-837 - Yali Xiang, Yun Xiong, Yangyong Zhu:
TI-GCN: A Dynamic Network Embedding Method with Time Interval Information. 838-847 - Zhe Xu, Si Zhang, Yinglong Xia, Liang Xiong, Hanghang Tong:
Ranking on Network of Heterogeneous Information Networks. 848-857 - Carl Yang, Liyuan Liu, Mengxiong Liu, Zongyi Wang, Chao Zhang, Jiawei Han:
Graph Clustering with Embedding Propagation. 858-867 - Yang Zhou, Jiaxiang Ren, Ruoming Jin, Zijie Zhang, Dejing Dou, Da Yan:
Unsupervised Multiple Network Alignment with Multinominal GAN and Variational Inference. 868-877 - Amir Abolfazli, Eirini Ntoutsi:
Drift-Aware Multi-Memory Model for Imbalanced Data Streams. 878-885 - Ankita Agarwal, Preetham Salehundam, Swati Padhee, William L. Romine, Tanvi Banerjee:
Leveraging Natural Language Processing to Mine Issues on Twitter During the COVID-19 Pandemic. 886-891 - Ali Assi, Mohamed Elati, Wajdi Dhifli:
Instance Matching in Knowledge Graphs Through Dynamic, Distributed and Affinity-Preserving Random Walk. 892-897 - Ting Bai, Youjie Zhang, Bin Wu, Jian-Yun Nie:
Temporal Graph Neural Networks for Social Recommendation. 898-903 - Chen Cui, Ning Yang, Philip S. Yu:
MLANE: Meta-Learning Based Adaptive Network Embedding. 904-909 - Minh-Son Dao, Ngoc-Thanh Nguyen, R. Uday Kiran, Koji Zettsu:
Fusion-3DCNN-max3P: A dynamic system for discovering patterns of predicted congestion. 910-915 - Takayasu Fushimi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient Computing of PageRank Scores on Exact Expected Transition Matrix of Large Uncertain Graph. 916-923 - Yang Gao, Yi-Fan Li, Yu Lin, Hemeng Tao, Latifur Khan:
A Simple, Effective and Extendible Approach to Deep Multi-task Learning. 924-929 - Maryam Habibi, Johannes Starlinger, Ulf Leser:
TabSim: A Siamese Neural Network for Accurate Estimation of Table Similarity. 930-937 - Zhixiang He, Chi-Yin Chow, Jia-Dong Zhang:
GAMIT: A New Encoder-Decoder Framework with Graphical Space and Multi-grained Time for Traffic Predictions. 938-943 - Minglin Hong, Xiaolin Li, Jing Wang, Haiyang He, Shiguo Huang:
A Hybrid Salient Object Detection with Global Context Awareness. 944-949