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ORCID30th KDD 2024: Barcelona, Spain
- Ricardo Baeza-Yates, Francesco Bonchi:
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2024, Barcelona, Spain, August 25-29, 2024. ACM 2024, ISBN 979-8-4007-0490-1
Keynote Talks
- Sanjeev Arora
:
From Word-prediction to Complex Skills: Compositional Thinking and Metacognition in LLMs. 1 - Tanya Y. Berger-Wolf:
AI for Nature: From Science to Impact. 2 - Xihong Lin:
Empower an End-to-end Scalable and Interpretable Data Science Ecosystem using Statistics, AI and Domain Science. 3-4
Research Track Papers
- Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, Ameet Deshpande:
GEO: Generative Engine Optimization. 5-16 - Andrea Agiollo, Young In Kim, Rajiv Khanna:
Approximating Memorization Using Loss Surface Geometry for Dataset Pruning and Summarization. 17-28 - Sara Ahmadian, MohammadHossein Bateni, Hossein Esfandiari, Silvio Lattanzi, Morteza Monemizadeh, Ashkan Norouzi-Fard:
Resilient k-Clustering. 29-38 - Amel Awadelkarim, Johan Ugander:
Statistical Models of Top-k Partial Orders. 39-48 - Amitoz Azad, Yuan Fang:
A Learned Generalized Geodesic Distance Function-Based Approach for Node Feature Augmentation on Graphs. 49-58 - Minyoung Bae, Yooju Shin, Youngeun Nam, Youngseop Lee, Jae-Gil Lee:
Semi-Supervised Learning for Time Series Collected at a Low Sampling Rate. 59-70 - Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Yangqiu Song:
Understanding Inter-Session Intentions via Complex Logical Reasoning. 71-82 - Yinhao Bai, Yuhua Zhao, Zhixin Han, Hang Gao, Chao Xue, Mengting Hu:
Towards Robust Information Extraction via Binomial Distribution Guided Counterpart Sequence. 83-94 - Yikun Ban, Yunzhe Qi, Tianxin Wei, Lihui Liu, Jingrui He:
Meta Clustering of Neural Bandits. 95-106 - MohammadHossein Bateni, Hossein Esfandiari, Samira HosseinGhorban, Alipasha Montaseri:
Improved Active Covering via Density-Based Space Transformation. 107-118 - Ali Behrouz, Farnoosh Hashemi:
Graph Mamba: Towards Learning on Graphs with State Space Models. 119-130 - Andrea Bernini, Fabrizio Silvestri, Gabriele Tolomei:
Evading Community Detection via Counterfactual Neighborhood Search. 131-140 - Tingzhu Bi, Yang Zhang, Yicheng Pan, Yu Zhang, Meng Ma, Xinrui Jiang, Linlin Han, Feng Wang, Xian Liu, Ping Wang:
FaultInsight: Interpreting Hyperscale Data Center Host Faults. 141-152 - Aurélien Bibaut, Winston Chou, Simon Ejdemyr, Nathan Kallus:
Learning the Covariance of Treatment Effects Across Many Weak Experiments. 153-162 - Filippo Brunelli, Pierluigi Crescenzi, Laurent Viennot:
Making Temporal Betweenness Computation Faster and Restless. 163-174 - Kunlin Cai, Jinghuai Zhang, Zhiqing Hong, William Shand, Guang Wang, Desheng Zhang, Jianfeng Chi, Yuan Tian:
Where Have You Been? A Study of Privacy Risk for Point-of-Interest Recommendation. 175-186 - Miaomiao Cai, Lei Chen, Yifan Wang, Haoyue Bai, Peijie Sun, Le Wu, Min Zhang, Meng Wang:
Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias. 187-198 - Tianchi Cai, Zhiwen Tan, Xierui Song, Tao Sun, Jiyan Jiang, Yunqi Xu, Yinger Zhang, Jinjie Gu:
FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering. 199-210 - Shuzhi Cao, Jianfei Ruan, Bo Dong, Bin Shi:
Tackling Instance-Dependent Label Noise with Class Rebalance and Geometric Regularization. 211-221 - Zongsheng Cao, Jing Li, Zigan Wang, Jinliang Li:
DiffusionE: Reasoning on Knowledge Graphs via Diffusion-based Graph Neural Networks. 222-230 - Heng Chang, Jiangnan Ye, Alejo Lopez-Avila, Jinhua Du, Jia Li:
Path-based Explanation for Knowledge Graph Completion. 231-242 - Tian-Yi Che, Xian-Ling Mao, Tian Lan, Heyan Huang:
A Hierarchical Context Augmentation Method to Improve Retrieval-Augmented LLMs on Scientific Papers. 243-254 - Jerry Chee, Shankar Kalyanaraman, Sindhu Kiranmai Ernala, Udi Weinsberg, Sarah Dean, Stratis Ioannidis:
Harm Mitigation in Recommender Systems under User Preference Dynamics. 255-265 - Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng:
Cluster-Wide Task Slowdown Detection in Cloud System. 266-277 - Jingbang Chen, Qiuyang Mang, Hangrui Zhou, Richard Peng, Yu Gao, Chenhao Ma:
Scalable Algorithm for Finding Balanced Subgraphs with Tolerance in Signed Networks. 278-287 - Jintai Chen, Jiahuan Yan, Qiyuan Chen, Danny Z. Chen, Jian Wu, Jimeng Sun:
Can a Deep Learning Model be a Sure Bet for Tabular Prediction? 288-296 - Junyang Chen, Yuzhu Ji, Rong Zou, Yiqun Zhang, Yiu-ming Cheung:
QGRL: Quaternion Graph Representation Learning for Heterogeneous Feature Data Clustering. 297-306 - Lin Chen, Fengli Xu, Nian Li, Zhenyu Han, Meng Wang, Yong Li, Pan Hui:
Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network. 307-318 - Meng Chen, Zechen Li, Weiming Huang, Yongshun Gong, Yilong Yin:
Profiling Urban Streets: A Semi-Supervised Prediction Model Based on Street View Imagery and Spatial Topology. 319-328 - Ming Chen, Weike Pan, Zhong Ming:
Explicit and Implicit Modeling via Dual-Path Transformer for Behavior Set-informed Sequential Recommendation. 329-340 - Mouxiang Chen, Lefei Shen, Han Fu, Zhuo Li, Jianling Sun, Chenghao Liu:
Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift. 341-352 - Nuo Chen, Yuhan Li, Jianheng Tang, Jia Li:
GraphWiz: An Instruction-Following Language Model for Graph Computational Problems. 353-364 - Tong Chen, Danny Wang, Xurong Liang, Marten Risius, Gianluca Demartini, Hongzhi Yin:
Hate Speech Detection with Generalizable Target-aware Fairness. 365-375 - Xiaocong Chen, Siyu Wang, Lina Yao:
Maximum-Entropy Regularized Decision Transformer with Reward Relabelling for Dynamic Recommendation. 376-384 - Yankai Chen, Quoc-Tuan Truong, Xin Shen, Jin Li, Irwin King:
Shopping Trajectory Representation Learning with Pre-training for E-commerce Customer Understanding and Recommendation. 385-396 - Zonghao Chen, Ruocheng Guo, Jean-Francois Ton, Yang Liu:
Conformal Counterfactual Inference under Hidden Confounding. 397-408 - Ke Cheng, Linzhi Peng, Pengyang Wang, Junchen Ye, Leilei Sun, Bowen Du:
DyGKT: Dynamic Graph Learning for Knowledge Tracing. 409-420 - Ke Cheng, Linzhi Peng, Junchen Ye, Leilei Sun, Bowen Du:
Co-Neighbor Encoding Schema: A Light-cost Structure Encoding Method for Dynamic Link Prediction. 421-432 - Yao Cheng, Caihua Shan, Yifei Shen, Xiang Li, Siqiang Luo, Dongsheng Li:
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise. 433-444 - Zhangtao Cheng, Jienan Zhang, Xovee Xu, Goce Trajcevski, Ting Zhong, Fan Zhou:
Retrieval-Augmented Hypergraph for Multimodal Social Media Popularity Prediction. 445-455 - Hongliang Chi, Yao Ma:
Enhancing Contrastive Learning on Graphs with Node Similarity. 456-465 - In-Koo Cho, Jonathan A. Libgober, Cheng Ding:
Iterative Weak Learnability and Multiclass AdaBoost. 466-477 - Martino Ciaperoni, Han Xiao, Aristides Gionis:
Efficient Exploration of the Rashomon Set of Rule-Set Models. 478-489 - Erica Coppolillo, Giuseppe Manco, Aristides Gionis:
Relevance Meets Diversity: A User-Centric Framework for Knowledge Exploration Through Recommendations. 490-501 - Jiajun Cui, Hong Qian, Bo Jiang, Wei Zhang:
Leveraging Pedagogical Theories to Understand Student Learning Process with Graph-based Reasonable Knowledge Tracing. 502-513 - Shuang Cui, Kai Han, Shaojie Tang, Feng Li, Jun Luo:
Fairness in Streaming Submodular Maximization Subject to a Knapsack Constraint. 514-525 - Sunhao Dai, Yuqi Zhou, Liang Pang, Weihao Liu, Xiaolin Hu, Yong Liu, Xiao Zhang, Gang Wang, Jun Xu:
Neural Retrievers are Biased Towards LLM-Generated Content. 526-537 - Siddhartha Shankar Das, S. M. Ferdous, Mahantesh M. Halappanavar, Edoardo Serra, Alex Pothen:
AGS-GNN: Attribute-guided Sampling for Graph Neural Networks. 538-549 - Thomas Decker, Alexander Koebler, Michael Lebacher, Ingo Thon, Volker Tresp, Florian Buettner:
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance. 550-561 - Yue Deng, Asadullah Hill Galib, Pang-Ning Tan, Lifeng Luo:
Unraveling Block Maxima Forecasting Models with Counterfactual Explanation. 562-573 - Kaize Ding, Xiaoxiao Ma, Yixin Liu, Shirui Pan:
Divide and Denoise: Empowering Simple Models for Robust Semi-Supervised Node Classification against Label Noise. 574-584 - Xueying Ding, Yue Zhao, Leman Akoglu:
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. 585-596 - Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang, Chengfei Lyu, Guihai Chen:
Enhancing On-Device LLM Inference with Historical Cloud-Based LLM Interactions. 597-608 - Manh Tuan Do, Kijung Shin:
Unsupervised Alignment of Hypergraphs with Different Scales. 609-620 - Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li:
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. 621-630 - Zheng Dong, Renhe Jiang, Haotian Gao, Hangchen Liu, Jinliang Deng, Qingsong Wen, Xuan Song:
Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting. 631-641 - Andrew F. Dreher, Etienne Vouga, Donald S. Fussell:
Estimated Judge Reliabilities for Weighted Bradley-Terry-Luce Are Not Reliable. 642-653 - Huaming Du, Long Shi, Xingyan Chen, Yu Zhao, Hegui Zhang, Carl Yang, Fuzhen Zhuang, Gang Kou:
Representation Learning of Temporal Graphs with Structural Roles. 654-665 - Kounianhua Du, Jizheng Chen, Jianghao Lin, Yunjia Xi, Hangyu Wang, Xinyi Dai, Bo Chen, Ruiming Tang, Weinan Zhang:
DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation. 666-676 - Yingpeng Du, Ziyan Wang, Zhu Sun, Yining Ma, Hongzhi Liu, Jie Zhang:
Disentangled Multi-interest Representation Learning for Sequential Recommendation. 677-688 - Haoran Duan, Cheng Xie, Linyu Li:
Reserving-Masking-Reconstruction Model for Self-Supervised Heterogeneous Graph Representation. 689-700 - Wenying Duan, Tianxiang Fang, Hong Rao, Xiaoxi He:
Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks. 701-712 - Avinava Dubey, Zhe Feng, Rahul Kidambi, Aranyak Mehta, Di Wang:
Auctions with LLM Summaries. 713-722 - Viet Duong, Qiong Wu, Zhengyi Zhou, Hongjue Zhao, Chenxiang Luo, Eric Zavesky, Huaxiu Yao, Huajie Shao:
CAT: Interpretable Concept-based Taylor Additive Models. 723-734 - Ruidong Fan, Xiao Ouyang, Hong Tao, Chenping Hou:
Label Shift Correction via Bidirectional Marginal Distribution Matching. 735-746 - Yi Fang, Dongzhe Fan, Daochen Zha, Qiaoyu Tan:
GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models. 747-758 - Shanshan Feng, Feiyu Meng, Lisi Chen, Shuo Shang, Yew Soon Ong:
ROTAN: A Rotation-based Temporal Attention Network for Time-Specific Next POI Recommendation. 759-770 - Yuting Feng, Vincent Y. F. Tan, Bogdan Cautis:
Influence Maximization via Graph Neural Bandits. 771-781 - Yuye Feng, Wei Zhang, Yao Fu, Weihao Jiang, Jiang Zhu, Wenqi Ren:
SensitiveHUE: Multivariate Time Series Anomaly Detection by Enhancing the Sensitivity to Normal Patterns. 782-793 - Zhiying Feng, Qiong Wu, Xu Chen:
Communication-efficient Multi-service Mobile Traffic Prediction by Leveraging Cross-service Correlations. 794-805 - Raphael Fischer, Amal Saadallah:
AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting. 806-815 - Kairui Fu, Shengyu Zhang, Zheqi Lv, Jingyuan Chen, Jiwei Li:
DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation. 816-826 - Xingbo Fu, Zihan Chen, Binchi Zhang, Chen Chen, Jundong Li:
Federated Graph Learning with Structure Proxy Alignment. 827-838 - Heyang Gao, Zexu Sun, Hao Yang, Xu Chen:
Policy-Based Bayesian Active Causal Discovery with Deep Reinforcement Learning. 839-850 - Xinyi Gao, Tong Chen, Wentao Zhang, Yayong Li, Xiangguo Sun, Hongzhi Yin:
Graph Condensation for Open-World Graph Learning. 851-862 - Yucen Gao, Zhehao Zhu, Mingqian Ma, Fei Gao, Hui Gao, Yangguang Shi, Xiaofeng Gao:
Online Preference Weight Estimation Algorithm with Vanishing Regret for Car-Hailing in Road Network. 863-871 - Ramin Ghorbani, Marcel J. T. Reinders, David M. J. Tax:
PATE: Proximity-Aware Time Series Anomaly Evaluation. 872-883 - Yong Liang Goh, Zhiguang Cao, Yining Ma, Yanfei Dong, Mohammed Haroon Dupty, Wee Sun Lee:
Hierarchical Neural Constructive Solver for Real-world TSP Scenarios. 884-895 - Jiahui Gong, Jingtao Ding, Fanjin Meng, Guilong Chen, Hong Chen, Shen Zhao, Haisheng Lu, Yong Li:
A Population-to-individual Tuning Framework for Adapting Pretrained LM to On-device User Intent Prediction. 896-907 - Zheng Gong, Ying Sun:
An Energy-centric Framework for Category-free Out-of-distribution Node Detection in Graphs. 908-919 - Zhibin Gu, Zhendong Li, Songhe Feng:
Topology-Driven Multi-View Clustering via Tensorial Refined Sigmoid Rank Minimization. 920-931 - Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang:
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. 932-943 - Linxin Guo, Yaochen Zhu, Min Gao, Yinghui Tao, Junliang Yu, Chen Chen:
Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations. 944-955 - Wentao Guo, Andrew Wang, Bradon Thymes, Thorsten Joachims:
Ranking with Slot Constraints. 956-967 - Zhuoning Guo, Duanyi Yao, Qiang Yang, Hao Liu:
HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning. 968-979 - Croix Gyurek, Niloy Talukder, Mohammad Al Hasan:
Binder: Hierarchical Concept Representation through Order Embedding of Binary Vectors. 980-991 - Do Heon Han, Nuno Moniz, Nitesh V. Chawla:
AnyLoss: Transforming Classification Metrics into Loss Functions. 992-1003 - Xiao Han, Chen Zhu, Xiao Hu, Chuan Qin, Xiangyu Zhao, Hengshu Zhu:
Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning. 1004-1015 - Kathrin Hanauer, Monika Henzinger, Robin Münk, Harald Räcke, Maximilian Vötsch:
Expander Hierarchies for Normalized Cuts on Graphs. 1016-1027 - Farnoosh Hashemi, Ali Behrouz:
A Unified Core Structure in Multiplex Networks: From Finding the Densest Subgraph to Modeling User Engagement. 1028-1039 - Xiang He, Wuyang Mao, Zhenghang Xu, Yuanzhe Gu, Yundu Huang, Zhonglin Zu, Liang Wang, Mengyu Zhao, Mengchuan Zou:
An Efficient Local Search Algorithm for Large GD Advertising Inventory Allocation with Multilinear Constraints. 1040-1049 - Yue He, Pengfei Tian, Renzhe Xu, Xinwei Shen, Xingxuan Zhang, Peng Cui:
Model-Agnostic Random Weighting for Out-of-Distribution Generalization. 1050-1061 - Zhuangzhuang He, Yifan Wang, Yonghui Yang, Peijie Sun, Le Wu, Haoyue Bai, Jinqi Gong, Richang Hong, Min Zhang:
Double Correction Framework for Denoising Recommendation. 1062-1072 - Marco Heyden, Vadim Arzamasov, Edouard Fouché, Klemens Böhm:
Budgeted Multi-Armed Bandits with Asymmetric Confidence Intervals. 1073-1084 - Yunbo Hou, Haoran Ye, Yingxue Zhang, Siyuan Xu, Guojie Song:
RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network. 1085-1095 - Ming Hu, Zhihao Yue, Xiaofei Xie, Cheng Chen, Yihao Huang, Xian Wei, Xiang Lian, Yang Liu, Mingsong Chen:
Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination. 1096-1107 - Qi Hu, Haoran Li, Jiaxin Bai, Zihao Wang, Yangqiu Song:
Privacy-Preserved Neural Graph Databases. 1108-1118 - Zhibo Hu, Chen Wang, Yanfeng Shu, Hye-Young Paik, Liming Zhu:
Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models. 1119-1130 - Renhong Huang, Jiarong Xu, Xin Jiang, Ruichuan An, Yang Yang:
Can Modifying Data Address Graph Domain Adaptation? 1131-1142 - Yihong Huang, Yuang Zhang, Liping Wang, Fan Zhang, Xuemin Lin:
EntropyStop: Unsupervised Deep Outlier Detection with Loss Entropy. 1143-1154 - Seonghyeon Hwang, Minsu Kim, Steven Euijong Whang:
RC-Mixup: A Data Augmentation Strategy against Noisy Data for Regression Tasks. 1155-1165 - Bulat Ibragimov, Gleb Gusev:
Learn Together Stop Apart: An Inclusive Approach to Ensemble Pruning. 1166-1176 - Bulat Ibragimov, Anton Vakhrushev:
Uplift Modelling via Gradient Boosting. 1177-1187 - Makoto Imamura, Takaaki Nakamura:
Efficient Discovery of Time Series Motifs under both Length Differences and Warping. 1188-1198 - Md Mouinul Islam, Soroush Vahidi, Baruch Schieber, Senjuti Basu Roy:
Promoting Fairness and Priority in Selecting k-Winners Using IRV. 1199-1210 - Jihyeong Jeon, Jiwon Park, Chanhee Park, U Kang:
FreQuant: A Reinforcement-Learning based Adaptive Portfolio Optimization with Multi-frequency Decomposition. 1211-1221