default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID26th KDD 2020: Virtual Conference, USA
- Rajesh Gupta, Yan Liu, Jiliang Tang, B. Aditya Prakash:
KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020. ACM 2020, ISBN 978-1-4503-7998-4
Keynote & Invited Talks
- Manuela Veloso:
AI for Intelligent Financial Services: Examples and Discussion. 1-2 - Emery N. Brown:
Keynote Speaker: Emery N. Brown. 3 - Yolanda Gil:
Keynote Speaker: Yolanda Gil. 4 - Alessandro Vespignani:
Keynote Speaker: Alessandro Vespignani. 5
Research Track Papers
- Ning Wu, Wayne Xin Zhao, Jingyuan Wang, Dayan Pan:
Learning Effective Road Network Representation with Hierarchical Graph Neural Networks. 6-14 - Jingyuan Wang, Yufan Wu, Mingxuan Li, Xin Lin, Junjie Wu, Chao Li:
Interpretability is a Kind of Safety: An Interpreter-based Ensemble for Adversary Defense. 15-24 - Aldo G. Carranza, Ryan A. Rossi, Anup Rao, Eunyee Koh:
Higher-order Clustering in Complex Heterogeneous Networks. 25-35 - Haoxing Lin, Rufan Bai, Weijia Jia, Xinyu Yang, Yongjian You:
Preserving Dynamic Attention for Long-Term Spatial-Temporal Prediction. 36-46 - Qifan Wang, Li Yang, Bhargav Kanagal, Sumit Sanghai, D. Sivakumar, Bin Shu, Zac Yu
, Jon Elsas:
Learning to Extract Attribute Value from Product via Question Answering: A Multi-task Approach. 47-55 - Liangyu Zhu, Wenbin Lu, Michael R. Kosorok, Rui Song:
Kernel Assisted Learning for Personalized Dose Finding. 56-65 - Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang:
Graph Structure Learning for Robust Graph Neural Networks. 66-74 - Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Weinan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola:
An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph. 75-84 - Nan Wang, Hongning Wang:
Directional Multivariate Ranking. 85-94 - Yue Wang, Ke Wang, Chunyan Miao:
Truth Discovery against Strategic Sybil Attack in Crowdsourcing. 95-104 - Gengyu Lyu, Songhe Feng, Yidong Li:
Partial Multi-Label Learning via Probabilistic Graph Matching Mechanism. 105-113 - Zhe Liu, Lina Yao, Lei Bai, Xianzhi Wang, Can Wang:
Spectrum-Guided Adversarial Disparity Learning. 114-124 - Yong He, Cheng Wang, Nan Li, Zhenyu Zeng:
Attention and Memory-Augmented Networks for Dual-View Sequential Learning. 125-134 - Lukas Pfahler, Katharina Morik:
Semantic Search in Millions of Equations. 135-143 - Kyuhan Lee, Hyeonsoo Jo, Jihoon Ko, Sungsu Lim, Kijung Shin:
SSumM: Sparse Summarization of Massive Graphs. 144-154 - Dawei Gao, Xiaoxi He, Zimu Zhou, Yongxin Tong, Ke Xu, Lothar Thiele:
Rethinking Pruning for Accelerating Deep Inference At the Edge. 155-164 - Hao-Jun Michael Shi, Dheevatsa Mudigere, Maxim Naumov, Jiyan Yang:
Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems. 165-175 - Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin:
Structural Patterns and Generative Models of Real-world Hypergraphs. 176-186 - Yasuhiro Fujiwara, Atsutoshi Kumagai, Sekitoshi Kanai, Yasutoshi Ida, Naonori Ueda:
Efficient Algorithm for the b-Matching Graph. 187-197 - Kai Ming Ting, Bi-Cun Xu, Takashi Washio, Zhi-Hua Zhou:
Isolation Distributional Kernel: A New Tool for Kernel based Anomaly Detection. 198-206 - Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Juncheng Liu, Bryan Hooi:
NodeAug: Semi-Supervised Node Classification with Data Augmentation. 207-217 - Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks. 218-228 - Hongyang Gao, Zhengyang Wang, Shuiwang Ji:
Kronecker Attention Networks. 229-237 - Thai Le, Suhang Wang, Dongwon Lee:
GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model's Prediction. 238-248 - Muhan Zhang, Christopher Ryan King, Michael Avidan, Yixin Chen:
Hierarchical Attention Propagation for Healthcare Representation Learning. 249-256 - Shengzhong Zhang, Zengfeng Huang, Haicang Zhou, Ziang Zhou:
SCE: Scalable Network Embedding from Sparsest Cut. 257-265 - Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiao Liu, Jun Huan, Xiang Zhang:
Local Community Detection in Multiple Networks. 266-274 - Ganzhao Yuan, Li Shen, Wei-Shi Zheng:
A Block Decomposition Algorithm for Sparse Optimization. 275-285 - Jian Liang, Bing Bai, Yuren Cao, Kun Bai, Fei Wang:
Adversarial Infidelity Learning for Model Interpretation. 286-296 - Zhihui Li, Xiaojun Chang, Lina Yao, Shirui Pan, Zongyuan Ge, Huaxiang Zhang:
Grounding Visual Concepts for Zero-Shot Event Detection and Event Captioning. 297-305 - Suman K. Bera, C. Seshadhri:
How to Count Triangles, without Seeing the Whole Graph. 306-316 - Jihoon Ko, Yunbum Kook, Kijung Shin:
Incremental Lossless Graph Summarization. 317-327 - Yufei Tao, Shangqi Lu:
From Online to Non-i.i.d. Batch Learning. 328-337 - Meng Liu, Hongyang Gao, Shuiwang Ji:
Towards Deeper Graph Neural Networks. 338-348 - Shenyang Huang, Yasmeen Hitti, Guillaume Rabusseau, Reihaneh Rabbany:
Laplacian Change Point Detection for Dynamic Graphs. 349-358 - Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi:
Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling. 359-367 - Kuo Zhong, Ying Wei, Chun Yuan, Haoli Bai, Junzhou Huang:
TranSlider: Transfer Ensemble Learning from Exploitation to Exploration. 368-378 - Jian Kang, Jingrui He, Ross Maciejewski, Hanghang Tong:
InFoRM: Individual Fairness on Graph Mining. 379-389 - Dongqi Fu, Dawei Zhou, Jingrui He:
Local Motif Clustering on Time-Evolving Graphs. 390-400 - Dawei Zhou, Lecheng Zheng, Jiawei Han, Jingrui He:
A Data-Driven Graph Generative Model for Temporal Interaction Networks. 401-411 - Xin Dai, Xiangnan Kong, Tian Guo, John Boaz Lee, Xinyue Liu, Constance M. Moore:
Recurrent Networks for Guided Multi-Attention Classification. 412-420 - Chao Li, Haoteng Tang, Cheng Deng, Liang Zhan, Wei Liu:
Vulnerability vs. Reliability: Disentangled Adversarial Examples for Cross-Modal Learning. 421-429 - Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji:
XGNN: Towards Model-Level Explanations of Graph Neural Networks. 430-438 - Xiang Li, Ben Kao, Caihua Shan, Dawei Yin, Martin Ester:
CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data. 439-449 - Xianli Zhang, Buyue Qian, Shilei Cao, Yang Li, Hang Chen, Yefeng Zheng, Ian Davidson:
INPREM: An Interpretable and Trustworthy Predictive Model for Healthcare. 450-460 - Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, Xia Hu:
Policy-GNN: Aggregation Optimization for Graph Neural Networks. 461-471 - Mengdi Huai, Jianhui Sun, Renqin Cai, Liuyi Yao, Aidong Zhang:
Malicious Attacks against Deep Reinforcement Learning Interpretations. 472-482 - Jianxin Ma, Chang Zhou, Hongxia Yang, Peng Cui, Xin Wang, Wenwu Zhu:
Disentangled Self-Supervision in Sequential Recommenders. 483-491 - Limeng Cui, Haeseung Seo, Maryam Tabar, Fenglong Ma, Suhang Wang, Dongwon Lee:
DETERRENT: Knowledge Guided Graph Attention Network for Detecting Healthcare Misinformation. 492-502 - Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, Christos Faloutsos:
MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals. 503-512 - Meghana Madhyastha, Gongkai Li, Veronika Strnadová-Neeley, James Browne, Joshua T. Vogelstein, Randal C. Burns, Carey E. Priebe:
Geodesic Forests. 513-523 - Zed Lee, Tony Lindgren, Panagiotis Papapetrou:
Z-Miner: An Efficient Method for Mining Frequent Arrangements of Event Intervals. 524-534 - Shaoxu Song, Yu Sun:
Imputing Various Incomplete Attributes via Distance Likelihood Maximization. 535-545 - Syeda Nahida Akter, Muhammad Abdullah Adnan:
WeightGrad: Geo-Distributed Data Analysis Using Quantization for Faster Convergence and Better Accuracy. 546-556 - Jing-Han Wu, Xuan Wu, Qing-Guo Chen, Yao Hu, Min-Ling Zhang:
Feature-Induced Manifold Disambiguation for Multi-View Partial Multi-label Learning. 557-565 - Haoyu Zhang, Qin Zhang:
MinSearch: An Efficient Algorithm for Similarity Search under Edit Distance. 566-576 - Aritra Konar, Nicholas D. Sidiropoulos:
Mining Large Quasi-cliques with Quality Guarantees from Vertex Neighborhoods. 577-587 - Junteng Jia, Austin R. Benson:
Residual Correlation in Graph Neural Network Regression. 588-598 - Yanying Li, Haipei Sun, Wendy Hui Wang:
Towards Fair Truth Discovery from Biased Crowdsourced Answers. 599-607 - Jiancheng Lyu, Shuai Zhang, Yingyong Qi, Jack Xin:
AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks. 608-616 - Chengxi Zang, Fei Wang:
MoFlow: An Invertible Flow Model for Generating Molecular Graphs. 617-626 - Yipeng Zhang, Bo Du, Lefei Zhang, Jia Wu:
Parallel DNN Inference Framework Leveraging a Compact RISC-V ISA-based Multi-core System. 627-635 - Yuxuan Zhao, Madeleine Udell:
Missing Value Imputation for Mixed Data via Gaussian Copula. 636-646 - Junyu Luo, Muchao Ye, Cao Xiao, Fenglong Ma:
HiTANet: Hierarchical Time-Aware Attention Networks for Risk Prediction on Electronic Health Records. 647-656 - Hanzhi Wang, Zhewei Wei, Junhao Gan, Sibo Wang, Zengfeng Huang:
Personalized PageRank to a Target Node, Revisited. 657-667 - Kenta Niwa, Noboru Harada, Guoqiang Zhang, W. Bastiaan Kleijn:
Edge-consensus Learning: Deep Learning on P2P Networks with Nonhomogeneous Data. 668-678 - Yi Liu, Hao Yuan, Lei Cai, Shuiwang Ji:
Deep Learning of High-Order Interactions for Protein Interface Prediction. 679-687 - Manqing Dong, Feng Yuan, Lina Yao, Xiwei Xu, Liming Zhu:
MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation. 688-697 - Lu Chen, Chengfei Liu, Rui Zhou, Jiajie Xu, Jeffrey Xu Yu, Jianxin Li:
Finding Effective Geo-social Group for Impromptu Activities with Diverse Demands. 698-708 - Yinan Mei, Shaoxu Song, Yunsu Lee, Jungho Park, Soo-Hyung Kim, Sungmin Yi:
Representing Temporal Attributes for Schema Matching. 709-719 - Kazuki Nakajima, Kazuyuki Shudo:
Estimating Properties of Social Networks via Random Walk considering Private Nodes. 720-730 - Zhongkai Hao, Chengqiang Lu, Zhenya Huang, Hao Wang, Zheyuan Hu, Qi Liu, Enhong Chen, Cheekong Lee:
ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. 731-752 - Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang:
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks. 753-763 - Corrado Monti, Gianmarco De Francisci Morales, Francesco Bonchi:
Learning Opinion Dynamics From Social Traces. 764-773 - Le Dai, Yu Yin, Chuan Qin, Tong Xu, Xiangnan He, Enhong Chen, Hui Xiong:
Enterprise Cooperation and Competition Analysis with a Sign-Oriented Preference Network. 774-782 - Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile:
BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals. 783-793 - Ting Li, Junbo Zhang, Kainan Bao, Yuxuan Liang, Yexin Li, Yu Zheng:
AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction. 794-802 - Junyi Gao, Cao Xiao, Lucas M. Glass, Jimeng Sun:
COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching. 803-812 - Jonas Fischer, Jilles Vreeken:
Discovering Succinct Pattern Sets Expressing Co-Occurrence and Mutual Exclusivity. 813-823 - Ang Li, Yixiao Duan, Huanrui Yang, Yiran Chen, Jianlei Yang:
TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework for Deep Learning with Anonymized Intermediate Representations. 824-832 - Wei Wen, Feng Yan, Yiran Chen, Hai Li:
AutoGrow: Automatic Layer Growing in Deep Convolutional Networks. 833-841 - Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo:
Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks. 842-852 - Pengyang Wang, Kunpeng Liu, Lu Jiang, Xiaolin Li, Yanjie Fu:
Incremental Mobile User Profiling: Reinforcement Learning with Spatial Knowledge Graph for Modeling Event Streams. 853-861 - Changchang Yin, Ruoqi Liu, Dongdong Zhang, Ping Zhang:
Identifying Sepsis Subphenotypes via Time-Aware Multi-Modal Auto-Encoder. 862-872 - Elias Chaibub Neto:
A Causal Look at Statistical Definitions of Discrimination. 873-881 - Mohammad Mahdi Kamani, Sadegh Farhang, Mehrdad Mahdavi, James Z. Wang:
Targeted Data-driven Regularization for Out-of-Distribution Generalization. 882-891 - Chengxi Zang, Fei Wang:
Neural Dynamics on Complex Networks. 892-902 - Guangrun Wang, Guangcong Wang, Keze Wang, Xiaodan Liang, Liang Lin:
Grammatically Recognizing Images with Tree Convolution. 903-912 - Yikun Ban, Jingrui He:
Generic Outlier Detection in Multi-Armed Bandit. 913-923 - Yingtong Dou, Guixiang Ma, Philip S. Yu, Sihong Xie:
Robust Spammer Detection by Nash Reinforcement Learning. 924-933 - Caleb Belth, Xinyi Zheng, Danai Koutra:
Mining Persistent Activity in Continually Evolving Networks. 934-944 - Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. 945-955 - Nicholas Gao, Max Wilson, Thomas Vandal, Walter Vinci, Ramakrishna R. Nemani, Eleanor Gilbert Rieffel:
High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder. 956-964 - Noveen Sachdeva, Yi Su, Thorsten Joachims:
Off-policy Bandits with Deficient Support. 965-975 - Ganqu Cui, Jie Zhou, Cheng Yang, Zhiyuan Liu:
Adaptive Graph Encoder for Attributed Graph Embedding. 976-985 - Si Zhang, Hanghang Tong, Yinglong Xia, Liang Xiong, Jiejun Xu:
NetTrans: Neural Cross-Network Transformation. 986-996 - Zhihao Jia, Sina Lin, Rex Ying, Jiaxuan You, Jure Leskovec, Alex Aiken:
Redundancy-Free Computation for Graph Neural Networks. 997-1005 - Kun Zhou, Wayne Xin Zhao, Shuqing Bian, Yuanhang Zhou, Ji-Rong Wen, Jingsong Yu:
Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion. 1006-1014 - Xiangyang Gou, Long He, Yinda Zhang, Ke Wang, Xilai Liu, Tong Yang, Yi Wang, Bin Cui:
Sliding Sketches: A Framework using Time Zones for Data Stream Processing in Sliding Windows. 1015-1025 - Yue Yu, Yinghao Li, Jiaming Shen, Hao Feng, Jimeng Sun, Chao Zhang:
STEAM: Self-Supervised Taxonomy Expansion with Mini-Paths. 1026-1035 - Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates:
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. 1036-1044 - Du Su, Hieu Tri Huynh, Ziao Chen, Yi Lu, Wenmiao Lu:
Re-identification Attack to Privacy-Preserving Data Analysis with Noisy Sample-Mean. 1045-1053 - Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang:
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. 1054-1064 - Qingqing Long, Yilun Jin, Guojie Song, Yi Li, Wei Lin:
Graph Structural-topic Neural Network. 1065-1073 - Guangxu Xun, Kishlay Jha, Jianhui Sun, Aidong Zhang:
Correlation Networks for Extreme Multi-label Text Classification. 1074-1082 - Le Yu, Leilei Sun, Bowen Du, Chuanren Liu, Hui Xiong, Weifeng Lv:
Predicting Temporal Sets with Deep Neural Networks. 1083-1091 - Bill Yuchen Lin, Ying Sheng, Nguyen Vo, Sandeep Tata:
FreeDOM: A Transferable Neural Architecture for Structured Information Extraction on Web Documents. 1092-1102 - Yao Zhang, Yun Xiong, Yun Ye, Tengfei Liu, Weiqiang Wang, Yangyong Zhu, Philip S. Yu:
SEAL: Learning Heuristics for Community Detection with Generative Adversarial Networks. 1103-1113 - Makoto Imamura, Takaaki Nakamura, Eamonn J. Keogh:
Matrix Profile XXI: A Geometric Approach to Time Series Chains Improves Robustness. 1114-1122 - Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian:
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks. 1123-1131 - Pan Peng, Yuichi Yoshida:
Average Sensitivity of Spectral Clustering. 1132-1140 - Wanli Shi, Victor S. Sheng, Xiang Li, Bin Gu:
Semi-Supervised Multi-Label Learning from Crowds via Deep Sequential Generative Model. 1141-1149 - Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, Jie Tang:
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. 1150-1160