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ORCID27th KDD 2021: Virtual Event, Singapore
- Feida Zhu, Beng Chin Ooi, Chunyan Miao:
KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, Singapore, August 14-18, 2021. ACM 2021, ISBN 978-1-4503-8332-5
Keynote Talks
- Vincent Conitzer:
Automated Mechanism Design for Strategic Classification: Abstract for KDD'21 Keynote Talk. 1 - Sharon C. Glotzer:
Data Science for Assembly Engineering. 2 - Claire J. Tomlin:
Safe Learning in Robotics. 3 - Jeffrey D. Ullman:
On the Nature of Data Science. 4
Research Track Papers
- Yanqing An, Qi Liu, Han Wu, Kai Zhang, Linan Yue, Mingyue Cheng, Hongke Zhao, Enhong Chen
:
LawyerPAN: A Proficiency Assessment Network for Trial Lawyers. 5-13 - Dawna Bagherian, James Gornet, Jeremy Bernstein, Yu-Li Ni, Yisong Yue, Markus Meister:
Fine-Grained System Identification of Nonlinear Neural Circuits. 14-24 - Bing Bai, Jian Liang, Guanhua Zhang, Hao Li, Kun Bai, Fei Wang:
Why Attentions May Not Be Interpretable? 25-34 - Yikun Ban, Jingrui He, Curtiss B. Cook:
Multi-facet Contextual Bandits: A Neural Network Perspective. 35-45 - Wei-Xuan Bao, Jun-Yi Hang, Min-Ling Zhang:
Partial Label Dimensionality Reduction via Confidence-Based Dependence Maximization. 46-54 - Artem Betlei, Eustache Diemert, Massih-Reza Amini:
Uplift Modeling with Generalization Guarantees. 55-65 - Arindam Bhattacharya, Sumanth Varambally, Amitabha Bagchi, Srikanta Bedathur:
Fast One-class Classification using Class Boundary-preserving Random Projections. 66-74 - Martin Bompaire, Alexandre Gilotte, Benjamin Heymann:
Causal Models for Real Time Bidding with Repeated User Interactions. 75-85 - Alexander Braylan, Matthew Lease:
Aggregating Complex Annotations via Merging and Matching. 86-94 - Chun-Hao Chang, Sarah Tan, Benjamin J. Lengerich, Anna Goldenberg, Rich Caruana:
How Interpretable and Trustworthy are GAMs? 95-105 - Hongjie Chen, Ryan A. Rossi, Kanak Mahadik, Sungchul Kim, Hoda Eldardiry:
Graph Deep Factors for Forecasting with Applications to Cloud Resource Allocation. 106-116 - Huiping Chen, Alessio Conte, Roberto Grossi, Grigorios Loukides, Solon P. Pissis, Michelle Sweering:
On Breaking Truss-Based Communities. 117-126 - Junjie Chen, Wendy Hui Wang, Hongchang Gao, Xinghua Shi:
PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks. 127-137 - Tong Chen, Hongzhi Yin, Yujia Zheng, Zi Huang, Yang Wang, Meng Wang:
Learning Elastic Embeddings for Customizing On-Device Recommenders. 138-147 - Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Causal Understanding of Fake News Dissemination on Social Media. 148-157 - Sohee Cho, Wonjoon Chang, Ginkyeng Lee, Jaesik Choi:
Interpreting Internal Activation Patterns in Deep Temporal Neural Networks by Finding Prototypes. 158-166 - Zhendong Chu, Hongning Wang:
Improve Learning from Crowds via Generative Augmentation. 167-175 - Zhixuan Chu, Stephen L. Rathbun, Sheng Li:
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data. 176-184 - Corinna Coupette, Jilles Vreeken:
Graph Similarity Description: How Are These Graphs Similar? 185-195 - Cyrus Cousins, Chloe Wohlgemuth, Matteo Riondato:
Bavarian: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages. 196-206 - Sen Cui, Weishen Pan, Changshui Zhang, Fei Wang:
Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility. 207-217 - Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang:
Labeled Data Generation with Inexact Supervision. 218-226 - Enyan Dai, Charu Aggarwal, Suhang Wang:
NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. 227-236 - Arka Daw, M. Maruf, Anuj Karpatne:
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics. 237-247 - Angus Dempster, Daniel F. Schmidt, Geoffrey I. Webb:
MiniRocket: A Very Fast (Almost) Deterministic Transform for Time Series Classification. 248-257 - Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu:
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. 258-268 - Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting. 269-278 - Yuhui Ding, Quanming Yao, Huan Zhao, Tong Zhang:
DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks. 279-288 - Jialin Dong, Da Zheng, Lin F. Yang, George Karypis:
Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs. 289-299 - Yushun Dong, Jian Kang, Hanghang Tong, Jundong Li:
Individual Fairness for Graph Neural Networks: A Ranking based Approach. 300-310 - Boxin Du, Lihui Liu, Hanghang Tong:
Sylvester Tensor Equation for Multi-Way Association. 311-321 - Lun Du, Fei Gao, Xu Chen, Ran Jia, Junshan Wang, Jiang Zhang, Shi Han, Dongmei Zhang:
TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data. 322-331 - Lukas Faber, Amin K. Moghaddam, Roger Wattenhofer:
When Comparing to Ground Truth is Wrong: On Evaluating GNN Explanation Methods. 332-341 - Jicong Fan:
Large-Scale Subspace Clustering via k-Factorization. 342-352 - Jinyuan Fang, Shangsong Liang, Zaiqiao Meng, Qiang Zhang:
Gaussian Process with Graph Convolutional Kernel for Relational Learning. 353-363 - Zheng Fang, Qingqing Long, Guojie Song, Kunqing Xie:
Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting. 364-373 - Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu:
Multiple-Instance Learning from Similar and Dissimilar Bags. 374-382 - Jonas Fischer, Jilles Vreeken:
Differentiable Pattern Set Mining. 383-392 - Tao-Yang Fu, Wang-Chien Lee:
ProgRPGAN: Progressive GAN for Route Planning. 393-403 - Tianfan Fu, Cao Xiao, Cheng Qian, Lucas M. Glass, Jimeng Sun:
Probabilistic and Dynamic Molecule-Disease Interaction Modeling for Drug Discovery. 404-414 - Chen Gao, Quanming Yao, Depeng Jin, Yong Li:
Efficient Data-specific Model Search for Collaborative Filtering. 415-425 - Ji Gao, Xiao Huang, Jundong Li:
Unsupervised Graph Alignment with Wasserstein Distance Discriminator. 426-435 - David García-Soriano, Francesco Bonchi:
Maxmin-Fair Ranking: Individual Fairness under Group-Fairness Constraints. 436-446 - Negin Golrezaei, Max Lin, Vahab S. Mirrokni, Hamid Nazerzadeh:
Boosted Second Price Auctions: Revenue Optimization for Heterogeneous Bidders. 447-457 - Ludmila Gordeeva, Vasily Ershov, Oleg Gulyaev, Igor Kuralenok:
Meaning Error Rate: ASR domain-specific metric framework. 458-466 - Jiewei Gu, Weiguo Zheng, Yuzheng Cai, Peng Peng:
Towards Computing a Near-Maximum Weighted Independent Set on Massive Graphs. 467-477 - Xiaotao Gu, Zihan Wang, Zhenyu Bi, Yu Meng, Liyuan Liu, Jiawei Han, Jingbo Shang:
UCPhrase: Unsupervised Context-aware Quality Phrase Tagging. 478-486 - Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Qi Zhang, Feng Kuang, Gao-Le Li, Zhang-Xun Liu, Guobin Wu, Nan Ma, Qun (Tracy) Li, Yufeng Li:
Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment. 487-495 - Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. 496-504 - Xiaojie Guo, Yuanqi Du, Liang Zhao:
Deep Generative Models for Spatial Networks. 505-515 - Xingzhi Guo, Baojian Zhou, Steven Skiena:
Subset Node Representation Learning over Large Dynamic Graphs. 516-526 - Nilesh Gupta, Sakina Bohra, Yashoteja Prabhu, Saurabh Purohit, Manik Varma:
Generalized Zero-Shot Extreme Multi-label Learning. 527-535 - Mahdi Hajiabadi, Jasbir Singh, Venkatesh Srinivasan, Alex Thomo:
Graph Summarization with Controlled Utility Loss. 536-546 - Liangzhe Han, Bowen Du, Leilei Sun, Yanjie Fu, Yisheng Lv, Hui Xiong:
Dynamic and Multi-faceted Spatio-temporal Deep Learning for Traffic Speed Forecasting. 547-555 - Peng Han, Jin Wang, Di Yao, Shuo Shang, Xiangliang Zhang:
A Graph-based Approach for Trajectory Similarity Computation in Spatial Networks. 556-564 - Xueting Han, Zhenhuan Huang, Bang An, Jing Bai:
Adaptive Transfer Learning on Graph Neural Networks. 565-574 - Bing He, Mustaque Ahamad, Srijan Kumar:
PETGEN: Personalized Text Generation Attack on Deep Sequence Embedding-based Classification Models. 575-584 - Xiaoxi He, Dawei Gao, Zimu Zhou, Yongxin Tong, Lothar Thiele:
Pruning-Aware Merging for Efficient Multitask Inference. 585-595 - Yue He, Peng Cui, Zheyan Shen, Renzhe Xu, Furui Liu, Yong Jiang:
DARING: Differentiable Causal Discovery with Residual Independence. 596-605 - Amin Heyrani Nobari, Wei Chen, Faez Ahmed:
PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design. 606-616 - Junyuan Hong, Zhuangdi Zhu, Shuyang Yu, Zhangyang Wang, Hiroko H. Dodge, Jiayu Zhou:
Federated Adversarial Debiasing for Fair and Transferable Representations. 617-627 - Yibo Hu, Latifur Khan:
Uncertainty-Aware Reliable Text Classification. 628-636 - Yun Hua, Xiangfeng Wang, Bo Jin, Wenhao Li, Junchi Yan, Xiaofeng He, Hongyuan Zha:
HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem. 637-645 - Han Huang, Leilei Sun, Bowen Du, Chuanren Liu, Weifeng Lv, Hui Xiong:
Representation Learning on Knowledge Graphs for Node Importance Estimation. 646-655 - Hao Huang, Yanan Peng, Ting Gan, Weiping Tu, Ruiting Zhou, Sai Wu:
Metric Learning via Penalized Optimization. 656-664 - Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, Jie Tang:
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. 665-674 - Zengfeng Huang, Shengzhong Zhang, Chong Xi, Tang Liu, Min Zhou:
Scaling Up Graph Neural Networks Via Graph Coarsening. 675-684 - Zexi Huang, Arlei Silva, Ambuj K. Singh:
A Broader Picture of Random-walk Based Graph Embedding. 685-695 - Zhenya Huang, Xin Lin, Hao Wang, Qi Liu, Enhong Chen, Jianhui Ma, Yu Su, Wei Tong:
DisenQNet: Disentangled Representation Learning for Educational Questions. 696-704 - Zijie Huang, Yizhou Sun, Wei Wang:
Coupled Graph ODE for Learning Interacting System Dynamics. 705-715 - Bo Hui, Da Yan, Haiquan Chen, Wei-Shinn Ku:
TrajNet: A Trajectory-Based Deep Learning Model for Traffic Prediction. 716-724 - Jun-Gi Jang, U Kang:
Fast and Memory-Efficient Tucker Decomposition for Answering Diverse Time Range Queries. 725-735 - Sheo Yon Jhin, Minju Jo, Taeyong Kong, Jinsung Jeon, Noseong Park:
ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations. 736-745 - Meng Jiang:
Cross-Network Learning with Partially Aligned Graph Convolutional Networks. 746-755 - Xunqiang Jiang, Tianrui Jia, Yuan Fang, Chuan Shi, Zhe Lin, Hui Wang:
Pre-training on Large-Scale Heterogeneous Graph. 756-766 - Zhe Jiang, Wenchong He, Marcus Stephen Kirby, Sultan Asiri, Da Yan:
Weakly Supervised Spatial Deep Learning based on Imperfect Vector Labels with Registration Errors. 767-775 - Ruoming Jin, Dong Li, Jing Gao, Zhi Liu, Li Chen, Yang Zhou:
Towards a Better Understanding of Linear Models for Recommendation. 776-785 - Jaehun Jung, Jinhong Jung, U Kang:
Learning to Walk across Time for Interpretable Temporal Knowledge Graph Completion. 786-795 - Shizuo Kaji, Akira Horiguchi, Takuro Abe, Yohsuke Watanabe:
A Hyper-surface Arrangement Model of Ranking Distributions. 796-804 - Dimitris Kalimeris, Smriti Bhagat, Shankar Kalyanaraman, Udi Weinsberg:
Preference Amplification in Recommender Systems. 805-815 - SeongKu Kang, Junyoung Hwang, Wonbin Kweon, Hwanjo Yu:
Topology Distillation for Recommender System. 829-839 - Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi:
Learning to Embed Categorical Features without Embedding Tables for Recommendation. 840-850 - Paris A. Karakasis, Aritra Konar, Nicholas D. Sidiropoulos:
Joint Graph Embedding and Alignment with Spectral Pivot. 851-859 - Vijay Keswani, L. Elisa Celis:
Auditing for Diversity Using Representative Examples. 860-870 - Jackson A. Killian, Arpita Biswas, Sanket Shah, Milind Tambe:
Q-Learning Lagrange Policies for Multi-Action Restless Bandits. 871-881 - Nicolas Klodt, Lars Seifert, Arthur Zahn, Katrin Casel, Davis Issac, Tobias Friedrich:
A Color-blind 3-Approximation for Chromatic Correlation Clustering and Improved Heuristics. 882-891 - Runze Lei, Pinghui Wang, Rundong Li, Peng Jia, Junzhou Zhao, Xiaohong Guan, Chao Deng:
Fast Rotation Kernel Density Estimation over Data Streams. 892-902 - Collin Leiber, Lena G. M. Bauer, Benjamin Schelling, Christian Böhm, Claudia Plant:
Dip-based Deep Embedded Clustering with k-Estimation. 903-913 - Duanshun Li, Jing Liu, Jinsung Jeon, Seoyoung Hong, Thai Le, Dongwon Lee, Noseong Park:
Large-Scale Data-Driven Airline Market Influence Maximization. 914-924 - Haoran Li, Yang Weng:
Physical Equation Discovery Using Physics-Consistent Neural Network (PCNN) Under Incomplete Observability. 925-933 - Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao:
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning. 934-942 - Jiayu Li, Hongyu Lu, Chenyang Wang, Weizhi Ma, Min Zhang, Xiangyu Zhao, Wei Qi, Yiqun Liu, Shaoping Ma:
A Difficulty-Aware Framework for Churn Prediction and Intervention in Games. 943-952 - Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu:
Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs. 953-963 - Shiju Li, Xin Huang, Chul-Ho Lee:
An Efficient and Scalable Algorithm for Estimating Kemeny's Constant of a Markov Chain on Large Graphs. 964-974 - Shuangli Li, Jingbo Zhou, Tong Xu, Liang Huang, Fan Wang, Haoyi Xiong, Weili Huang, Dejing Dou, Hui Xiong:
Structure-aware Interactive Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinity. 975-985 - Tianbo Li, Tianze Luo, Yiping Ke, Sinno Jialin Pan:
Mitigating Performance Saturation in Neural Marked Point Processes: Architectures and Loss Functions. 986-994 - Xin-Chun Li, De-Chuan Zhan:
FedRS: Federated Learning with Restricted Softmax for Label Distribution Non-IID Data. 995-1005 - Xuejun Liao, Patrick Koch, Shunping Huang, Yan Xu:
Efficient Collaborative Filtering via Data Augmentation and Step-size Optimization. 1006-1016 - Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian:
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport. 1017-1026 - Yi-Shan Lin, Wen-Chuan Lee, Z. Berkay Celik:
What Do You See?: Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors. 1027-1035 - Bingyu Liu, Yuhong Guo, Jianan Jiang, Jian Tang, Weihong Deng:
Multi-view Correlation based Black-box Adversarial Attack for 3D Object Detection. 1036-1044 - Brian Liu, Miaolan Xie, Madeleine Udell:
ControlBurn: Feature Selection by Sparse Forests. 1045-1054 - Danyang Liu, Jianxun Lian, Zheng Liu, Xiting Wang, Guangzhong Sun, Xing Xie:
Reinforced Anchor Knowledge Graph Generation for News Recommendation Reasoning. 1055-1065 - Haoxin Liu, Ziwei Zhang, Peng Cui, Yafeng Zhang, Qiang Cui, Jiashuo Liu, Wenwu Zhu:
Signed Graph Neural Network with Latent Groups. 1066-1075 - Jialu Liu, Tianqi Liu, Cong Yu:
NewsEmbed: Modeling News through Pre-trained Document Representations. 1076-1086 - Lihui Liu, Boxin Du, Heng Ji, ChengXiang Zhai, Hanghang Tong:
Neural-Answering Logical Queries on Knowledge Graphs. 1087-1097 - Qi Liu, Jin Zhang, Defu Lian, Yong Ge, Jianhui Ma, Enhong Chen:
Online Additive Quantization. 1098-1108 - Zemin Liu, Trung-Kien Nguyen, Yuan Fang:
Tail-GNN: Tail-Node Graph Neural Networks. 1109-1119 - Zhuo Liu, Yanxuan Li, Xingzhi Sun, Fei Wang, Gang Hu, Guotong Xie:
Dialogue Based Disease Screening Through Domain Customized Reinforcement Learning. 1120-1128 - Qingqing Long, Lingjun Xu, Zheng Fang, Guojie Song:
HGK-GNN: Heterogeneous Graph Kernel based Graph Neural Networks. 1129-1138 - Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Yunfeng Zhang, Karthikeyan Shanmugam, Chun-Chen Tu:
Leveraging Latent Features for Local Explanations. 1139-1149 - Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jianguo Jiang, Yuxiao Dong, Jie Tang:
Are we really making much progress?: Revisiting, benchmarking and refining heterogeneous graph neural networks. 1150-1160 - Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang:
Graph Adversarial Attack via Rewiring. 1161-1169