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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 - Meghana Madhyastha, Kunal Lillaney, James Browne, Joshua T. Vogelstein, Randal C. Burns:
BLOCKSET (Block-Aligned Serialized Trees): Reducing Inference Latency for Tree ensemble Deployment. 1170-1179 - Neil G. Marchant, Benjamin I. P. Rubinstein:
Needle in a Haystack: Label-Efficient Evaluation under Extreme Class Imbalance. 1180-1190 - Maxwell J. McNeil, Lin Zhang, Petko Bogdanov:
Temporal Graph Signal Decomposition. 1191-1201 - Chuizheng Meng, Sirisha Rambhatla, Yan Liu:
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling. 1202-1211 - Mike A. Merrill, Ge Zhang, Tim Althoff:
MULTIVERSE: Mining Collective Data Science Knowledge from Code on the Web to Suggest Alternative Analysis Approaches. 1212-1222 - Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Susie Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang:
DeGNN: Improving Graph Neural Networks with Graph Decomposition. 1223-1233 - Anasua Mitra, Priyesh Vijayan, Sanasam Ranbir Singh, Diganta Goswami, Srinivasan Parthasarathy, Balaraman Ravindran:
Semi-Supervised Deep Learning for Multiplex Networks. 1234-1244 - Nicholas Monath, Kumar Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu:
Scalable Hierarchical Agglomerative Clustering. 1245-1255 - Sofia Maria Nikolakaki, Alina Ene, Evimaria Terzi:
An Efficient Framework for Balancing Submodularity and Cost. 1256-1266 - Leslie O'Bray, Bastian Rieck, Karsten M. Borgwardt:
Filtration Curves for Graph Representation. 1267-1275 - Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima:
Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. 1276-1286 - Weishen Pan, Sen Cui, Jiang Bian, Changshui Zhang, Fei Wang:
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition. 1287-1297 - Guansong Pang, Anton van den Hengel, Chunhua Shen, Longbing Cao:
Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data. 1298-1308 - Yong-chan Park, Jun-Gi Jang, U Kang:
Fast and Accurate Partial Fourier Transform for Time Series Data. 1309-1318 - Noujan Pashanasangi, C. Seshadhri:
Faster and Generalized Temporal Triangle Counting, via Degeneracy Ordering. 1319-1328 - Pan Peng, Daniel Lopatta, Yuichi Yoshida, Gramoz Goranci:
Local Algorithms for Estimating Effective Resistance. 1329-1338 - Ninh Pham:
Simple Yet Efficient Algorithms for Maximum Inner Product Search via Extreme Order Statistics. 1339-1347 - Giulia Preti, Gianmarco De Francisci Morales, Matteo Riondato:
MaNIACS: Approximate Mining of Frequent Subgraph Patterns through Sampling. 1348-1358 - Xin Qian, Ryan A. Rossi, Fan Du, Sungchul Kim, Eunyee Koh, Sana Malik, Tak Yeon Lee, Joel Chan:
Learning to Recommend Visualizations from Data. 1359-1369 - Huiling Qin, Xianyuan Zhan, Yuanxun Li, Xiaodu Yang, Yu Zheng:
Network-Wide Traffic States Imputation Using Self-interested Coalitional Learning. 1370-1378 - Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Ruiming Tang, Xiuqiang He, Yong Yu:
Retrieval & Interaction Machine for Tabular Data Prediction. 1379-1389 - Liang Qu, Huaisheng Zhu, Ruiqi Zheng, Yuhui Shi, Hongzhi Yin:
ImGAGN: Imbalanced Network Embedding via Generative Adversarial Graph Networks. 1390-1398 - Thibaud Rahier, Amélie Héliou, Matthieu Martin, Christophe Renaudin, Eustache Diemert:
Individual Treatment Prescription Effect Estimation in a Low Compliance Setting. 1399-1409 - Huimin Ren, Sijie Ruan, Yanhua Li, Jie Bao, Chuishi Meng, Ruiyuan Li, Yu Zheng:
MTrajRec: Map-Constrained Trajectory Recovery via Seq2Seq Multi-task Learning. 1410-1419 - Dawid Rymarczyk, Lukasz Struski, Jacek Tabor, Bartosz Zielinski:
ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification. 1420-1430 - Ylli Sadikaj, Yllka Velaj, Sahar Behzadi, Claudia Plant:
Spectral Clustering of Attributed Multi-relational Graphs. 1431-1440 - Karishma Sharma, Yizhou Zhang, Emilio Ferrara, Yan Liu:
Identifying Coordinated Accounts on Social Media through Hidden Influence and Group Behaviours. 1441-1451 - Shuanghong Shen, Qi Liu, Enhong Chen, Zhenya Huang, Wei Huang, Yu Yin, Yu Su, Shijin Wang:
Learning Process-consistent Knowledge Tracing. 1452-1460 - Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter:
Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes. 1461-1469 - Kaushik Sinha, Parikshit Ram:
Fruit-fly Inspired Neighborhood Encoding for Classification. 1470-1480 - Hanyu Song, Peizhao Li, Hongfu Liu:
Deep Clustering based Fair Outlier Detection. 1481-1489 - Hwanjun Song, Minseok Kim, Dongmin Park, Yooju Shin, Jae-Gil Lee:
Robust Learning by Self-Transition for Handling Noisy Labels. 1490-1500 - Konstantinos Sotiropoulos, Charalampos E. Tsourakakis:
Triangle-aware Spectral Sparsifiers and Community Detection. 1501-1509 - Olivier Sprangers, Sebastian Schelter, Maarten de Rijke:
Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression. 1510-1520 - Felix I. Stamm, Martin Becker, Markus Strohmaier, Florian Lemmerich:
Redescription Model Mining. 1521-1529 - Jianhui Sun, Ying Yang, Guangxu Xun, Aidong Zhang:
A Stagewise Hyperparameter Scheduler to Improve Generalization. 1530-1540 - Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma:
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. 1541-1551 - Shulong Tan, Zhaozhuo Xu, Weijie Zhao, Hongliang Fei, Zhixin Zhou, Ping Li:
Norm Adjusted Proximity Graph for Fast Inner Product Retrieval. 1552-1560 - Qi Tian, Kun Kuang, Kelu Jiang, Fei Wu, Yisen Wang:
Analysis and Applications of Class-wise Robustness in Adversarial Training. 1561-1570 - Kiran Tomlinson, Johan Ugander, Austin R. Benson:
Choice Set Confounding in Discrete Choice. 1571-1581 - Kiran Tomlinson, Austin R. Benson:
Learning Interpretable Feature Context Effects in Discrete Choice. 1582-1592 - Veronica Tozzo, Federico Ciech, Davide Garbarino, Alessandro Verri:
Statistical Models Coupling Allows for Complex Local Multivariate Time Series Analysis. 1593-1603 - Nate Veldt, Austin R. Benson, Jon M. Kleinberg:
The Generalized Mean Densest Subgraph Problem. 1604-1614 - Praveen Venkateswaran, Vinod Muthusamy, Vatche Isahagian, Nalini Venkatasubramanian:
Environment Agnostic Invariant Risk Minimization for Classification of Sequential Datasets. 1615-1624 - Friedhelm Victor, Cuneyt Gurcan Akcora, Yulia R. Gel, Murat Kantarcioglu:
Alphacore: Data Depth based Core Decomposition. 1625-1633 - Runzhe Wan, Xinyu Zhang, Rui Song:
Multi-Objective Model-based Reinforcement Learning for Infectious Disease Control. 1634-1644 - Binghui Wang, Jinyuan Jia, Xiaoyu Cao, Neil Zhenqiang Gong:
Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation. 1645-1653 - Binghui Wang, Jiayi Guo, Ang Li, Yiran Chen, Hai Li:
Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective. 1667-1676 - Ding Wang, Pang-Ning Tan:
JOHAN: A Joint Online Hurricane Trajectory and Intensity Forecasting Framework. 1677-1685 - Hanzhi Wang, Mingguo He, Zhewei Wei, Sibo Wang, Ye Yuan, Xiaoyong Du, Ji-Rong Wen:
Approximate Graph Propagation. 1686-1696 - Hongwei Wang, Hongyu Ren, Jure Leskovec:
Relational Message Passing for Knowledge Graph Completion. 1697-1707 - Qitong Wang, Themis Palpanas:
Deep Learning Embeddings for Data Series Similarity Search. 1708-1716 - Wenjie Wang, Fuli Feng, Xiangnan He, Xiang Wang, Tat-Seng Chua:
Deconfounded Recommendation for Alleviating Bias Amplification. 1717-1725 - Xiao Wang, Nian Liu, Hui Han, Chuan Shi:
Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning. 1726-1736 - Yaqing Wang, Subhabrata Mukherjee, Haoda Chu, Yuancheng Tu, Ming Wu, Jing Gao, Ahmed Hassan Awadallah:
Meta Self-training for Few-shot Neural Sequence Labeling. 1737-1747 - Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi:
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. 1748-1757 - Zheng Wang, Cheng Long, Gao Cong, Qianru Zhang:
Error-Bounded Online Trajectory Simplification with Multi-Agent Reinforcement Learning. 1758-1768 - Zheng Wang, Jialong Wang, Yuchen Guo, Zhiguo Gong:
Zero-shot Node Classification with Decomposed Graph Prototype Network. 1769-1779 - Zhiruo Wang, Haoyu Dong, Ran Jia, Jia Li, Zhiyi Fu, Shi Han, Dongmei Zhang:
TUTA: Tree-based Transformers for Generally Structured Table Pre-training. 1780-1790 - Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi, Xiangnan He:
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System. 1791-1800 - Tong Wei, Jiang-Xin Shi, Yufeng Li:
Probabilistic Label Tree for Streaming Multi-Label Learning. 1801-1811 - Tong Wei, Wei-Wei Tu, Yufeng Li, Guo-Ping Yang:
Towards Robust Prediction on Tail Labels. 1812-1820 - Zeyi Wen, Zhishang Zhou, Hanfeng Liu, Bingsheng He, Xia Li, Jian Chen:
Enhancing SVMs with Problem Context Aware Pipeline. 1821-1829 - Chenwang Wu, Defu Lian, Yong Ge, Zhihao Zhu, Enhong Chen:
Triple Adversarial Learning for Influence based Poisoning Attack in Recommender Systems. 1830-1840 - Dongxia Wu, Liyao Gao, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Yi-An Ma, Rose Yu:
Quantifying Uncertainty in Deep Spatiotemporal Forecasting. 1841-1851 - Jun Wu, Jingrui He:
Indirect Invisible Poisoning Attacks on Domain Adaptation. 1852-1862 - Yuhan Wu, Zirui Liu, Xiang Yu, Jie Gui, Haochen Gan, Yuhao Han, Tao Li, Ori Rottenstreich, Tong Yang:
MapEmbed: Perfect Hashing with High Load Factor and Fast Update. 1863-1872 - Tian Xia, Wei-Shinn Ku:
Geometric Graph Representation Learning on Protein Structure Prediction. 1873-1883 - Wenwen Xia, Yuchen Li, Jianwei Tian, Shenghong Li:
Forecasting Interaction Order on Temporal Graphs. 1884-1893 - Teng Xiao, Zhengyu Chen, Donglin Wang, Suhang Wang:
Learning How to Propagate Messages in Graph Neural Networks. 1894-1903 - Ming-Kun Xie, Feng Sun, Sheng-Jun Huang:
Partial Multi-Label Learning with Meta Disambiguation. 1904-1912 - Hao Xiong, Junchi Yan, Li Pan:
Contrastive Multi-View Multiplex Network Embedding with Applications to Robust Network Alignment. 1913-1923 - Depeng Xu, Wei Du, Xintao Wu:
Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent. 1924-1932 - Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Jian Li, Tao Qin, Tie-Yan Liu:
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search. 1933-1943 - Hao Xue, Flora D. Salim:
Exploring Self-Supervised Representation Ensembles for COVID-19 Cough Classification. 1944-1952 - Chaoqi Yang, Navjot Singh, Cao Xiao, Cheng Qian, Edgar Solomonik, Jimeng Sun:
MTC: Multiresolution Tensor Completion from Partial and Coarse Observations. 1953-1963 - Fan Yang, Sahan Suresh Alva, Jiahao Chen, Xia Hu:
Model-Based Counterfactual Synthesizer for Interpretation. 1964-1974 - Menglin Yang, Min Zhou, Marcus Kalander, Zengfeng Huang, Irwin King:
Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space. 1975-1985 - Qingping Yang, Yixuan Cao, Hongwei Li, Ping Luo:
Numerical Formula Recognition from Tables. 1986-1996 - Yazheng Yang, Boyuan Pan, Deng Cai, Huan Sun:
TopNet: Learning from Neural Topic Model to Generate Long Stories. 1997-2005 - Yueji Yang, Yuchen Li, Panagiotis Karras, Anthony K. H. Tung:
Context-aware Outstanding Fact Mining from Knowledge Graphs. 2006-2016 - Hang Yin, John Boaz Lee, Xiangnan Kong, Thomas Hartvigsen, Sihong Xie:
Energy-Efficient Models for High-Dimensional Spike Train Classification using Sparse Spiking Neural Networks. 2017-2025 - Yu Yin, Ke Chen, Lidan Shou, Gang Chen:
Defending Privacy Against More Knowledgeable Membership Inference Attackers. 2026-2036 - Jaemin Yoo, Yejun Soun, Yong-chan Park, U Kang:
Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts. 2037-2045 - Minji Yoon, Théophile Gervet, Baoxu Shi, Sufeng Niu, Qi He, Jaewon Yang:
Performance-Adaptive Sampling Strategy Towards Fast and Accurate Graph Neural Networks. 2046-2056 - Ansheng You, Xiangzeng Zhou, Yingya Zhang, Pan Pan, Yinghui Xu:
Extremely Compact Non-local Representation Learning. 2057-2065 - Fuxun Yu, Weishan Zhang, Zhuwei Qin, Zirui Xu, Di Wang, Chenchen Liu, Zhi Tian, Xiang Chen:
Fed2: Feature-Aligned Federated Learning. 2066-2074 - Hong Yu, Jia Tang, Guoyin Wang, Xinbo Gao:
A Novel Multi-View Clustering Method for Unknown Mapping Relationships Between Cross-View Samples. 2075-2083 - Junliang Yu, Hongzhi Yin, Min Gao, Xin Xia, Xiangliang Zhang, Nguyen Quoc Viet Hung:
Socially-Aware Self-Supervised Tri-Training for Recommendation. 2084-2092 - Bo-Wen Yuan, Yu-Sheng Li, Pengrui Quan, Chih-Jen Lin:
Efficient Optimization Methods for Extreme Similarity Learning with Nonlinear Embeddings. 2093-2103 - Qingkai Zeng, Jinfeng Lin, Wenhao Yu, Jane Cleland-Huang, Meng Jiang:
Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations. 2104-2113 - George Zerveas, Srideepika Jayaraman, Dhaval Patel, Anuradha Bhamidipaty, Carsten Eickhoff:
A Transformer-based Framework for Multivariate Time Series Representation Learning. 2114-2124 - Ruohan Zhan, Vitor Hadad, David A. Hirshberg, Susan Athey:
Off-Policy Evaluation via Adaptive Weighting with Data from Contextual Bandits. 2125-2135 - Chao Zhang, Reza Akbarinia, Farouk Toumani:
Efficient Incremental Computation of Aggregations over Sliding Windows. 2136-2144 - Denghui Zhang, Zixuan Yuan, Yanchi Liu, Hao Liu, Fuzhen Zhuang, Hui Xiong, Haifeng Chen:
Domain-oriented Language Modeling with Adaptive Hybrid Masking and Optimal Transport Alignment. 2145-2153 - Hengtong Zhang, Changxin Tian, Yaliang Li, Lu Su, Nan Yang, Wayne Xin Zhao, Jing Gao:
Data Poisoning Attack against Recommender System Using Incomplete and Perturbed Data. 2154-2164 - Hengtong Zhang, Jing Gao, Lu Su:
Data Poisoning Attacks Against Outcome Interpretations of Predictive Models. 2165-2173 - Huayi Zhang, Lei Cao, Peter M. VanNostrand, Samuel Madden, Elke A. Rundensteiner:
ELITE: Robust Deep Anomaly Detection with Meta Gradient. 2174-2182 - Jiawen Zhang, Jiaqi Zhu, Yi Yang, Wandong Shi, Congcong Zhang, Hongan Wang:
Knowledge-Enhanced Domain Adaptation in Few-Shot Relation Classification. 2183-2191 - Le Zhang, Ding Zhou, Hengshu Zhu, Tong Xu, Rui Zha, Enhong Chen, Hui Xiong:
Attentive Heterogeneous Graph Embedding for Job Mobility Prediction. 2192-2201 - Shengming Zhang, Hao Zhong, Zixuan Yuan, Hui Xiong:
Scalable Heterogeneous Graph Neural Networks for Predicting High-potential Early-stage Startups. 2202-2211 - Si Zhang, Hanghang Tong, Long Jin, Yinglong Xia, Yunsong Guo:
Balancing Consistency and Disparity in Network Alignment. 2212-2222 - Sixiao Zhang, Hongxu Chen, Xiao Ming, Lizhen Cui, Hongzhi Yin, Guandong Xu:
Where are we in embedding spaces? 2223-2231 - Wentao Zhang, Yuezihan Jiang, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, Bin Cui:
ROD: Reception-aware Online Distillation for Sparse Graphs. 2232-2242 - Xingyi Zhang, Kun Xie, Sibo Wang, Zengfeng Huang:
Learning Based Proximity Matrix Factorization for Node Embedding. 2243-2253 - Yi Zhang, Yu Zhang, Wei Wang:
Multi-Task Learning via Generalized Tensor Trace Norm. 2254-2262 - Yinan Zhang, Boyang Li, Yong Liu, Hao Wang, Chunyan Miao:
Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems. 2263-2273 - Zhen Zhang, Jiajun Bu, Martin Ester, Zhao Li, Chengwei Yao, Zhi Yu, Can Wang:
H2MN: Graph Similarity Learning with Hierarchical Hypergraph Matching Networks. 2274-2284 - Bohan Zhao, Xiang Li, Boyu Tian, Zhiyu Mei, Wenfei Wu:
DHS: Adaptive Memory Layout Organization of Sketch Slots for Fast and Accurate Data Stream Processing. 2285-2293 - Chen Zhao, Feng Chen, Bhavani Thuraisingham:
Fairness-Aware Online Meta-learning. 2294-2304 - Junzhou Zhao, Pinghui Wang, Chao Deng, Jing Tao:
Temporal Biased Streaming Submodular Optimization. 2305-2315 - Yikai Zhao, Zheng Zhong, Yuanpeng Li, Yi Zhou, Yifan Zhu, Li Chen, Yi Wang, Tong Yang:
Cluster-Reduce: Compressing Sketches for Distributed Data Streams. 2316-2326 - Yuhai Zhao, Yejiang Wang, Zhengkui Wang, Chengqi Zhang:
Multi-graph Multi-label Learning with Dual-granularity Labeling. 2327-2337 - Jiawei Zheng, Qianli Ma, Hao Gu, Zhenjing Zheng:
Multi-view Denoising Graph Auto-Encoders on Heterogeneous Information Networks for Cold-start Recommendation. 2338-2348 - Weiguo Zheng, Yifan Yang, Chengzhi Piao:
Accelerating Set Intersections over Graphs by Reducing-Merging. 2349-2359 - Wenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang:
Knowledge is Power: Hierarchical-Knowledge Embedded Meta-Learning for Visual Reasoning in Artistic Domains. 2360-2368 - Mingze Zhong, Hong Xie, Qingsheng Zhu:
Quantifying Assimilate-Contrast Effects in Online Rating Systems: Modeling, Analysis and Application. 2369-2377 - Haoyi Zhou, Jianxin Li, Jieqi Peng, Shuai Zhang, Shanghang Zhang:
Triplet Attention: Rethinking the Similarity in Transformers. 2378-2388 - Mengyu Zhou, Qingtao Li, Xinyi He, Yuejiang Li, Yibo Liu, Wei Ji, Shi Han, Yining Chen, Daxin Jiang, Dongmei Zhang:
Table2Charts: Recommending Charts by Learning Shared Table Representations. 2389-2399 - Xiaotian Zhou, Zhongzhi Zhang:
Maximizing Influence of Leaders in Social Networks. 2400-2408 - Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Körpeoglu, Kannan Achan, Jingrui He:
PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network. 2409-2419 - Yuqiang Zhou, Qi Liu, Jinze Wu, Fei Wang, Zhenya Huang, Wei Tong, Hui Xiong, Enhong Chen, Jianhui Ma:
Modeling Context-aware Features for Cognitive Diagnosis in Student Learning. 2420-2428 - Zhengze Zhou, Giles Hooker, Fei Wang:
S-LIME: Stabilized-LIME for Model Explanation. 2429-2438 - Ziwei Zhu, Yun He, Xing Zhao, James Caverlee:
Popularity Bias in Dynamic Recommendation. 2439-2449 - Xu Zou, Da Yin, Qingyang Zhong, Hongxia Yang, Zhilin Yang, Jie Tang:
Controllable Generation from Pre-trained Language Models via Inverse Prompting. 2450-2460 - Xu Zou, Qinkai Zheng, Yuxiao Dong, Xinyu Guan, Evgeny Kharlamov, Jialiang Lu, Jie Tang:
TDGIA: Effective Injection Attacks on Graph Neural Networks. 2461-2471
ADS Track Papers
- Ahmed Abdulaal, Zhuanghua Liu, Tomer Lancewicki:
Practical Approach to Asynchronous Multivariate Time Series Anomaly Detection and Localization. 2485-2494 - Carlo Abrate, Francesco Bonchi:
Counterfactual Graphs for Explainable Classification of Brain Networks. 2495-2504 - Aniruddha Adiga, Lijing Wang, Benjamin Hurt, Akhil Sai Peddireddy, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan Leroy Lewis, Madhav V. Marathe:
All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting. 2505-2513 - Spurthi Amba Hombaiah, Tao Chen, Mingyang Zhang, Michael Bendersky, Marc Najork:
Dynamic Language Models for Continuously Evolving Content. 2514-2524 - Sihem Amer-Yahia, Shady Elbassuoni, Ahmad Ghizzawi, Anas Hosami:
Quantifying and Addressing Ranking Disparity in Human-Powered Data Acquisition. 2525-2533 - Ching-Yuan Bai, Hsuan-Tien Lin, Colin Raffel, Wendy Chi-wen Kan:
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition. 2534-2542 - Amin Banitalebi-Dehkordi, Naveen Vedula, Jian Pei, Fei Xia, Lanjun Wang, Yong Zhang:
Auto-Split: A General Framework of Collaborative Edge-Cloud AI. 2543-2553 - Guy Barshatski, Kira Radinsky:
Unpaired Generative Molecule-to-Molecule Translation for Lead Optimization. 2554-2564 - João Bento, Pedro Saleiro, André Ferreira Cruz, Mário A. T. Figueiredo, Pedro Bizarro:
TimeSHAP: Explaining Recurrent Models through Sequence Perturbations. 2565-2573 - Hodaya Binyamini, Ron Bitton, Masaki Inokuchi, Tomohiko Yagyu, Yuval Elovici, Asaf Shabtai:
A Framework for Modeling Cyber Attack Techniques from Security Vulnerability Descriptions. 2574-2583 - Fedor Borisyuk, Siddarth Malreddy, Jun Mei, Yiqun Liu, Xiaoyi Liu, Piyush Maheshwari, Anthony Bell, Kaushik Rangadurai:
VisRel: Media Search at Scale. 2584-2592 - Karim Bouyarmane:
GEM: Translation-Free Zero-Shot Global Entity Matcher for Global Catalogs. 2593-2600 - Léa Briand, Guillaume Salha-Galvan, Walid Bendada, Mathieu Morlon, Viet-Anh Tran:
A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Apps. 2601-2609 - Chu Cao, Mo Li:
Generating Mobility Trajectories with Retained Data Utility. 2610-2620 - Gromit Yeuk-Yin Chan, Tung Mai, Anup B. Rao, Ryan A. Rossi, Fan Du, Cláudio T. Silva, Juliana Freire:
Interactive Audience Expansion On Large Scale Online Visitor Data. 2621-2631 - Serina Chang, Mandy L. Wilson, Bryan L. Lewis, Zakaria Mehrab, Komal K. Dudakiya, Emma Pierson, Pang Wei Koh, Jaline Gerardin, Beth Redbird, David Grusky, Madhav V. Marathe, Jure Leskovec:
Supporting COVID-19 Policy Response with Large-scale Mobility-based Modeling. 2632-2642 - Wei-Cheng Chang, Daniel L. Jiang, Hsiang-Fu Yu, Choon-Hui Teo, Jiong Zhang, Kai Zhong, Kedarnath Kolluri, Qie Hu, Nikhil Shandilya, Vyacheslav Ievgrafov, Japinder Singh, Inderjit S. Dhillon:
Extreme Multi-label Learning for Semantic Matching in Product Search. 2643-2651 - Chaochao Chen, Jun Zhou, Li Wang, Xibin Wu, Wenjing Fang, Jin Tan, Lei Wang, Alex X. Liu, Hao Wang, Cheng Hong:
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control. 2652-2662 - Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao, Weinan Zhang, Xiawei Guo, Jian Shen, Yanru Qu, Jieli Lu, Min Xu, Yu Xu, Tiange Wang, Mian Li, Weiwei Tu, Yong Yu, Yufang Bi, Weiqing Wang, Guang Ning:
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction. 2663-2673 - Stephen Xi Chen, Saurajit Mukherjee, Unmesh Phadke, Tingting Wang, Junwon Park, Ravi Theja Yada:
Web-Scale Generic Object Detection at Microsoft Bing. 2674-2682 - Yifei Chen, Haoyu Ma, Jiangyuan Wang, Jianbao Wu, Xian Wu, Xiaohui Xie:
PD-Net: Quantitative Motor Function Evaluation for Parkinson's Disease via Automated Hand Gesture Analysis. 2683-2691 - Yudong Chen, Xin Wang, Miao Fan, Jizhou Huang, Shengwen Yang, Wenwu Zhu:
Curriculum Meta-Learning for Next POI Recommendation. 2692-2702 - Ka Ho Chow, Ling Liu:
Robust Object Detection Fusion Against Deception. 2703-2713 - Farhan Asif Chowdhury, M. Ashraf Siddiquee, Glenn Eli Baker, Abdullah Mueen:
FASER: Seismic Phase Identifier for Automated Monitoring. 2714-2721 - Graham Cormode, Abhinav Mishra, Joseph Ross, Pavel Veselý:
Theory meets Practice at the Median: A Worst Case Comparison of Relative Error Quantile Algorithms. 2722-2731 - Snehil Dahiya, Shalini Sharma, Dhruv Sahnan, Vasu Goel, Emilie Chouzenoux, Víctor Elvira, Angshul Majumdar, Anil Bandhakavi, Tanmoy Chakraborty:
Would Your Tweet Invoke Hate on the Fly? Forecasting Hate Intensity of Reply Threads on Twitter. 2732-2742 - Alex Deng, Yicheng Li, Jiannan Lu, Vivek Ramamurthy:
On Post-selection Inference in A/B Testing. 2743-2752 - Qilin Deng, Hao Li, Kai Wang, Zhipeng Hu, Runze Wu, Linxia Gong, Jianrong Tao, Changjie Fan, Peng Cui:
Globally Optimized Matchmaking in Online Games. 2753-2763 - Amin Dhaou, Antoine Bertoncello, Sébastien Gourvénec, Josselin Garnier, Erwan Le Pennec:
Causal and Interpretable Rules for Time Series Analysis. 2764-2772 - Rashed Doha, Mohammad Al Hasan, Sohel Anwar, Veera Rajendran:
Deep Learning based Crop Row Detection with Online Domain Adaptation. 2773-2781 - David Dohan, Andreea Gane, Maxwell L. Bileschi, David Belanger, Lucy J. Colwell:
Improving Protein Function Annotation via Unsupervised Pre-training: Robustness, Efficiency, and Insights. 2782-2791 - Chao Du, Zhifeng Gao, Shuo Yuan, Lining Gao, Ziyan Li, Yifan Zeng, Xiaoqiang Zhu, Jian Xu, Kun Gai, Kuang-Chih Lee:
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning. 2792-2801 - Alessandro Epasto, Andrés Muñoz Medina, Steven Avery, Yijian Bai, Róbert Busa-Fekete, CJ Carey, Ya Gao, David Guthrie, Subham Ghosh, James Ioannidis, Junyi Jiao, Jakub Lacki, Jason Lee, Arne Mauser, Brian Milch, Vahab S. Mirrokni, Deepak Ravichandran, Wei Shi, Max Spero, Yunting Sun, Umar Syed, Sergei Vassilvitskii, Shuo Wang:
Clustering for Private Interest-based Advertising. 2802-2810 - Lev Faivishevsky, Adi Szeskin, Ashwin K. Muppalla, Ravid Shwartz-Ziv, Itamar Ben-Ari, Ronen Laperdon, Benjamin Melloul, Tahi Hollander, Tom Hope, Amitai Armon:
Automated Testing of Graphics Units by Deep-Learning Detection of Visual Anomalies. 2811-2821 - Miao Fan, Yibo Sun, Jizhou Huang, Haifeng Wang, Ying Li:
Meta-Learned Spatial-Temporal POI Auto-Completion for the Search Engine at Baidu Maps. 2822-2830 - Yujie Fan, Mingxuan Ju, Shifu Hou, Yanfang Ye, Wenqiang Wan, Kui Wang, Yinming Mei, Qi Xiong:
Heterogeneous Temporal Graph Transformer: An Intelligent System for Evolving Android Malware Detection. 2831-2839 - Xiaomin Fang, Jizhou Huang, Fan Wang, Lihang Liu, Yibo Sun, Haifeng Wang:
SSML: Self-Supervised Meta-Learner for En Route Travel Time Estimation at Baidu Maps. 2840-2848 - Zhihan Fang, Guang Yang, Dian Zhang, Xiaoyang Xie, Guang Wang, Yu Yang, Fan Zhang, Desheng Zhang:
MoCha: Large-Scale Driving Pattern Characterization for Usage-based Insurance. 2849-2857 - Cheng Feng, Pengwei Tian:
Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering. 2858-2867 - Ivan Fursov, Matvey Morozov, Nina Kaploukhaya, Elizaveta Kovtun, Rodrigo Rivera-Castro, Gleb Gusev, Dmitry Babaev, Ivan Kireev, Alexey Zaytsev, Evgeny Burnaev:
Adversarial Attacks on Deep Models for Financial Transaction Records. 2868-2878 - Chengliang Gao, Fan Zhang, Guanqun Wu, Qiwan Hu, Qiang Ru, Jinghua Hao, Renqing He, Zhizhao Sun:
A Deep Learning Method for Route and Time Prediction in Food Delivery Service. 2879-2889 - Siyu Gu, Xiang-Rong Sheng, Ying Fan, Guorui Zhou, Xiaoqiang Zhu:
Real Negatives Matter: Continuous Training with Real Negatives for Delayed Feedback Modeling. 2890-2898 - Ziyu Guan, Hongchang Wu, Qingyu Cao, Hao Liu, Wei Zhao, Sheng Li, Cai Xu, Guang Qiu, Jian Xu, Bo Zheng:
Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search. 2899-2909 - Huifeng Guo, Bo Chen, Ruiming Tang, Weinan Zhang, Zhenguo Li, Xiuqiang He:
An Embedding Learning Framework for Numerical Features in CTR Prediction. 2910-2918 - Liyi Guo, Junqi Jin, Haoqi Zhang, Zhenzhe Zheng, Zhiye Yang, Zhizhuang Xing, Fei Pan, Lvyin Niu, Fan Wu, Haiyang Xu, Chuan Yu, Yuning Jiang, Xiaoqiang Zhu:
We Know What You Want: An Advertising Strategy Recommender System for Online Advertising. 2919-2927 - Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney:
Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism. 2928-2936 - Benjamin Han, Carl Arndt:
Budget Allocation as a Multi-Agent System of Contextual & Continuous Bandits. 2937-2945 - Junheng Hao, Chuan Lei, Vasilis Efthymiou, Abdul Quamar, Fatma Özcan, Yizhou Sun, Wei Wang:
MEDTO: Medical Data to Ontology Matching Using Hybrid Graph Neural Networks. 2946-2954 - Qianyue Hao, Fengli Xu, Lin Chen, Pan Hui, Yong Li:
Hierarchical Reinforcement Learning for Scarce Medical Resource Allocation with Imperfect Information. 2955-2963 - Xiaobo Hao, Yudan Liu, Ruobing Xie, Kaikai Ge, Linyao Tang, Xu Zhang, Leyu Lin:
Adversarial Feature Translation for Multi-domain Recommendation. 2964-2973 - Michaela Hardt, Xiaoguang Chen, Xiaoyi Cheng, Michele Donini, Jason Gelman, Satish Gollaprolu, John He, Pedro Larroy, Xinyu Liu, Nick McCarthy, Ashish Rathi, Scott Rees, Amaresh Ankit Siva, ErhYuan Tsai, Keerthan Vasist, Pinar Yilmaz, Muhammad Bilal Zafar, Sanjiv Das, Kevin Haas, Tyler Hill, Krishnaram Kenthapadi:
Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud. 2974-2983 - Helia Hashemi, Aasish Pappu, Mi Tian, Praveen Chandar, Mounia Lalmas, Benjamin A. Carterette:
Neural Instant Search for Music and Podcast. 2984-2992 - Yue He, Xiujun Chen, Di Wu, Junwei Pan, Qing Tan, Chuan Yu, Jian Xu, Xiaoqiang Zhu:
A Unified Solution to Constrained Bidding in Online Display Advertising. 2993-3001 - Yue He, Yancheng Dong, Peng Cui, Yuhang Jiao, Xiaowei Wang, Ji Liu, Philip S. Yu:
Purify and Generate: Learning Faithful Item-to-Item Graph from Noisy User-Item Interaction Behaviors. 3002-3010 - James Hong, Will Crichton, Haotian Zhang, Daniel Y. Fu, Jacob Ritchie, Jeremy Barenholtz, Ben Hannel, Xinwei Yao, Michaela Murray, Geraldine Moriba, Maneesh Agrawala, Kayvon Fatahalian:
Analysis of Faces in a Decade of US Cable TV News. 3011-3021 - Junhao Hua, Ling Yan, Huan Xu, Cheng Yang:
Markdowns in E-Commerce Fresh Retail: A Counterfactual Prediction and Multi-Period Optimization Approach. 3022-3031 - Jizhou Huang, Haifeng Wang, Yibo Sun, Miao Fan, Zhengjie Huang, Chunyuan Yuan, Yawen Li:
HGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps. 3032-3040 - Yanhua Huang, Weikun Wang, Lei Zhang, Ruiwen Xu:
Sliding Spectrum Decomposition for Diversified Recommendation. 3041-3049 - Yuzhen Huang, Xiaohan Wei, Xing Wang, Jiyan Yang, Bor-Yiing Su, Shivam Bharuka, Dhruv Choudhary, Zewei Jiang, Hai Zheng, Jack Langman:
Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters. 3050-3058 - Zai Huang, Mingyuan Tao, Bufeng Zhang:
Deep Inclusion Relation-aware Network for User Response Prediction at Fliggy. 3059-3067 - Johannes Huegle, Christopher Hagedorn, Michael Perscheid, Hasso Plattner:
MPCSL - A Modular Pipeline for Causal Structure Learning. 3068-3076 - Kishlay Jha, Guangxu Xun, Nan Du, Aidong Zhang:
Knowledge-Guided Efficient Representation Learning for Biomedical Domain. 3077-3085 - Heinrich Jiang, Maya R. Gupta:
Bootstrapping for Batch Active Sampling. 3086-3096 - Wenqi Jiang, Zhenhao He, Shuai Zhang, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso:
FleetRec: Large-Scale Recommendation Inference on Hybrid GPU-FPGA Clusters. 3097-3105 - Brian Karrer, Liang Shi, Monica Bhole, Matt Goldman, Tyrone Palmer, Charlie Gelman, Mikael Konutgan, Feng Sun:
Network Experimentation at Scale. 3106-3116 - Yaniv Katz, Oded Vainas:
Addressing Non-Representative Surveys using Multiple Instance Learning. 3117-3127 - Peeyush Kumar, Ranveer Chandra, Chetan Bansal, Shivkumar Kalyanaraman, Tanuja Ganu, Michael Grant:
Micro-climate Prediction - Multi Scale Encoder-decoder based Deep Learning Framework. 3128-3138 - Lang Lang, Zhenlong Zhu, Xuanye Liu, Jianxin Zhao, Jixing Xu, Minghui Shan:
Architecture and Operation Adaptive Network for Online Recommendations. 3139-3149 - Changhun Lee, Soohyeok Kim, Chiehyeon Lim, Jayun Kim, Yeji Kim, Minyoung Jung:
Diet Planning with Machine Learning: Teacher-forced REINFORCE for Composition Compliance with Nutrition Enhancement. 3150-3160 - Chenyi Lei, Yong Liu, Lingzi Zhang, Guoxin Wang, Haihong Tang, Houqiang Li, Chunyan Miao:
SEMI: A Sequential Multi-Modal Information Transfer Network for E-Commerce Micro-Video Recommendations. 3161-3171 - Pan Li, Zhichao Jiang, Maofei Que, Yao Hu, Alexander Tuzhilin:
Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction. 3172-3180 - Sen Li, Fuyu Lv, Taiwei Jin, Guli Lin, Keping Yang, Xiaoyi Zeng, Xiao-Ming Wu, Qianli Ma:
Embedding-based Product Retrieval in Taobao Search. 3181-3189 - Siqing Li, Liuyi Yao, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Tonglei Guo, Bolin Ding, Ji-Rong Wen:
Debiasing Learning based Cross-domain Recommendation. 3190-3199 - Xiao-Hui Li, Yuhan Shi, Haoyang Li, Wei Bai, Caleb Chen Cao, Lei Chen:
An Experimental Study of Quantitative Evaluations on Saliency Methods. 3200-3208 - Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui:
OpenBox: A Generalized Black-box Optimization Service. 3209-3219 - Zhihan Li, Youjian Zhao, Jiaqi Han, Ya Su, Rui Jiao, Xidao Wen, Dan Pei:
Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding. 3220-3230 - Shining Liang, Ming Gong, Jian Pei, Linjun Shou, Wanli Zuo, Xianglin Zuo, Daxin Jiang:
Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition. 3231-3239 - Xiao Liang, Zheng Yang, Binghui Wang, Shaofeng Hu, Zijie Yang, Dong Yuan, Neil Zhenqiang Gong, Qi Li, Fang He:
Unveiling Fake Accounts at the Time of Registration: An Unsupervised Approach. 3240-3250 - Junyang Lin, Rui Men, An Yang, Chang Zhou, Yichang Zhang, Peng Wang, Jingren Zhou, Jie Tang, Hongxia Yang:
M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining. 3251-3261 - Rongmei Lin, Xiang He, Jie Feng, Nasser Zalmout, Yan Liang, Li Xiong, Xin Luna Dong:
PAM: Understanding Product Images in Cross Product Category Attribute Extraction. 3262-3270 - Wenqing Lin:
Large-Scale Network Embedding in Apache Spark. 3271-3279 - Can Liu, Li Sun, Xiang Ao, Jinghua Feng, Qing He, Hao Yang:
Intention-aware Heterogeneous Graph Attention Networks for Fraud Transactions Detection. 3280-3288 - Hao Liu, Qian Gao, Jiang Li, Xiaochao Liao, Hao Xiong, Guangxing Chen, Wenlin Wang, Guobao Yang, Zhiwei Zha, Daxiang Dong, Dejing Dou, Haoyi Xiong:
JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu. 3289-3298 - Juan Liu, Lei Pei, Ying Sun, Heather Simpson, Jocelyn Lu, Nhung Ho:
Categorization of Financial Transactions in QuickBooks. 3299-3307 - Lihui Liu, Boxin Du, Yi Ren Fung, Heng Ji, Jiejun Xu, Hanghang Tong:
KompaRe: A Knowledge Graph Comparative Reasoning System. 3308-3318 - Min Liu, Jialiang Mao, Kang Kang:
Trustworthy and Powerful Online Marketplace Experimentation with Budget-split Design. 3319-3329 - Shuncheng Liu, Han Su, Yan Zhao, Kai Zeng, Kai Zheng:
Lane Change Scheduling for Autonomous Vehicle: A Prediction-and-Search Framework. 3343-3353 - Xiangyu Liu, Chuan Yu, Zhilin Zhang, Zhenzhe Zheng, Yu Rong, Hongtao Lv, Da Huo, Yiqing Wang, Dagui Chen, Jian Xu, Fan Wu, Guihai Chen, Xiaoqiang Zhu:
Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising. 3354-3364 - Yiding Liu, Weixue Lu, Suqi Cheng, Daiting Shi, Shuaiqiang Wang, Zhicong Cheng, Dawei Yin:
Pre-trained Language Model for Web-scale Retrieval in Baidu Search. 3365-3375 - Yiqun Liu, Kaushik Rangadurai, Yunzhong He, Siddarth Malreddy, Xunlong Gui, Xiaoyi Liu, Fedor Borisyuk:
Que2Search: Fast and Accurate Query and Document Understanding for Search at Facebook. 3376-3384 - Xusheng Luo, Le Bo, Jinhang Wu, Lin Li, Zhiy Luo, Yonghua Yang, Keping Yang:
AliCoCo2: Commonsense Knowledge Extraction, Representation and Application in E-commerce. 3385-3393 - Charbel Merhej, Ryan J. Beal, Tim Matthews, Sarvapali D. Ramchurn:
What Happened Next? Using Deep Learning to Value Defensive Actions in Football Event-Data. 3394-3403 - Shaunak Mishra, Mikhail Kuznetsov, Gaurav Srivastava, Maxim Sviridenko:
VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Search. 3404-3413 - Rajarshee Mitra, Rhea Jain, Aditya Srikanth Veerubhotla, Manish Gupta:
Zero-shot Multi-lingual Interrogative Question Generation for "People Also Ask" at Bing. 3414-3422 - Akash Kumar Mohankumar, Nikit Begwani, Amit Singh:
Diversity driven Query Rewriting in Search Advertising. 3423-3431 - Andrea Nestler, Nour Karessli, Karl Hajjar, Rodrigo Weffer, Reza Shirvany:
SizeFlags: Reducing Size and Fit Related Returns in Fashion E-Commerce. 3432-3440 - Fei Ni, Jianye Hao, Jiawen Lu, Xialiang Tong, Mingxuan Yuan, Jiahui Duan, Yi Ma, Kun He:
A Multi-Graph Attributed Reinforcement Learning based Optimization Algorithm for Large-scale Hybrid Flow Shop Scheduling Problem. 3441-3451 - Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt, Stefan Feuerriegel:
AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units. 3452-3462 - Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cédric Archambeau:
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization. 3463-3471 - Yukun Ping, Chen Gao, Taichi Liu, Xiaoyi Du, Hengliang Luo, Depeng Jin, Yong Li:
User Consumption Intention Prediction in Meituan. 3472-3482 - Zhen Qin, Honglei Zhuang, Rolf Jagerman, Xinyu Qian, Po Hu, Dan Chary Chen, Xuanhui Wang, Michael Bendersky, Marc Najork:
Bootstrapping Recommendations at Chrome Web Store. 3483-3491 - Rohan Ramanath, Konstantin Salomatin, Jeffrey D. Gee, Kirill Talanine, Onkar Dalal, Gungor Polatkan, Sara Smoot, Deepak Kumar:
Lambda Learner: Fast Incremental Learning on Data Streams. 3492-3502 - Houxing Ren, Jingyuan Wang, Wayne Xin Zhao, Ning Wu:
RAPT: Pre-training of Time-Aware Transformer for Learning Robust Healthcare Representation. 3503-3511 - Pieter Robberechts, Jan Van Haaren, Jesse Davis:
A Bayesian Approach to In-Game Win Probability in Soccer. 3512-3521 - Sandra Sajeev, Jade Huang, Nikos Karampatziakis, Matthew Hall, Sebastian Kochman, Weizhu Chen:
Contextual Bandit Applications in a Customer Support Bot. 3522-3530 - Amray Schwabe, Joel Persson, Stefan Feuerriegel:
Predicting COVID-19 Spread from Large-Scale Mobility Data. 3531-3539 - Ignacio Segovia-Dominguez, Huikyo Lee, Yuzhou Chen, Michael J. Garay, Krzysztof M. Gorski, Yulia R. Gel:
Does Air Quality Really Impact COVID-19 Clinical Severity: Coupling NASA Satellite Datasets with Geometric Deep Learning. 3540-3548 - Dingyuan Shi, Yongxin Tong, Zimu Zhou, Bingchen Song, Weifeng Lv, Qiang Yang:
Learning to Assign: Towards Fair Task Assignment in Large-Scale Ride Hailing. 3549-3557 - Oliver Snow, Hossein Sharifi-Noghabi, Jialin Lu, Olga I. Zolotareva, Mark Lee, Martin Ester:
Interpretable Drug Response Prediction using a Knowledge-based Neural Network. 3558-3568 - Sukhdeep S. Sodhi, Ellie Ka In Chio, Ambarish Jash, Santiago Ontañón, Ajit Apte, Ankit Kumar, Ayooluwakunmi Jeje, Dima Kuzmin, Harry Fung, Heng-Tze Cheng, Jon Effrat, Tarush Bali, Nitin Jindal, Pei Cao, Sarvjeet Singh, Senqiang Zhou, Tameen Khan, Amol Wankhede, Moustafa Alzantot, Allen Wu, Tushar Chandra:
Mondegreen: A Post-Processing Solution to Speech Recognition Error Correction for Voice Search Queries. 3569-3575 - Maya Srikanth, Anqi Liu, Nicholas Adams-Cohen, Jian Cao, R. Michael Alvarez, Anima Anandkumar:
Dynamic Social Media Monitoring for Fast-Evolving Online Discussions. 3576-3584 - Mengying Sun, Jing Xing, Huijun Wang, Bin Chen, Jiayu Zhou:
MoCL: Data-driven Molecular Fingerprint via Knowledge-aware Contrastive Learning from Molecular Graph. 3585-3594 - Maryam Tabar, Jared Gluck, Anchit Goyal, Fei Jiang, Derek Morr, Annalyse Kehs, Dongwon Lee, David P. Hughes, Amulya Yadav:
A PLAN for Tackling the Locust Crisis in East Africa: Harnessing Spatiotemporal Deep Models for Locust Movement Forecasting. 3595-3604 - Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye:
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms. 3605-3615 - Ha Xuan Tran, Thuc Duy Le, Jiuyong Li, Lin Liu, Jixue Liu, Yanchang Zhao, Tony Waters:
Recommending the Most Effective Intervention to Improve Employment for Job Seekers with Disability. 3616-3626 - Martin Valdez-Vivas, Varun Sharma, Nick Stanisha, Shan Li, Luo Mi, Wei Jiang, Alex Kalinin, Josh Metzler:
Clockwork: A Delay-Based Global Scheduling Framework for More Consistent Landing Times in the Data Warehouse. 3627-3637 - Andrew Z. Wang, Rex Ying, Pan Li, Nikhil Rao, Karthik Subbian, Jure Leskovec:
Bipartite Dynamic Representations for Abuse Detection. 3638-3648 - Chengyu Wang, Haojie Pan, Yuan Liu, Kehan Chen, Minghui Qiu, Wei Zhou, Jun Huang, Haiqing Chen, Wei Lin, Deng Cai:
MeLL: Large-scale Extensible User Intent Classification for Dialogue Systems with Meta Lifelong Learning. 3649-3659 - Guang Wang, Zhou Qin, Shuai Wang, Huijun Sun, Zheng Dong, Desheng Zhang:
Record: Joint Real-Time Repositioning and Charging for Electric Carsharing with Dynamic Deadlines. 3660-3669 - Haishuai Wang, Zhao Li, Peng Zhang, Jiaming Huang, Pengrui Hui, Jian Liao, Ji Zhang, Jiajun Bu:
Live-Streaming Fraud Detection: A Heterogeneous Graph Neural Network Approach. 3670-3678 - Hao Wang, Chi Harold Liu, Zipeng Dai, Jian Tang, Guoren Wang:
Energy-Efficient 3D Vehicular Crowdsourcing for Disaster Response by Distributed Deep Reinforcement Learning. 3679-3687 - Jiachen Wang, Dazhen Deng, Xiao Xie, Xinhuan Shu, Yu-Xuan Huang, Le-Wen Cai, Hui Zhang, Min-Ling Zhang, Zhi-Hua Zhou, Yingcai Wu:
Tac-Valuer: Knowledge-based Stroke Evaluation in Table Tennis. 3688-3696 - Xiting Wang, Xinwei Gu, Jie Cao, Zihua Zhao, Yulan Yan, Bhuvan Middha, Xing Xie:
Reinforcing Pretrained Models for Generating Attractive Text Advertisements. 3697-3707 - Yaqing Wang, Fenglong Ma, Haoyu Wang, Kishlay Jha, Jing Gao:
Multimodal Emergent Fake News Detection via Meta Neural Process Networks. 3708-3716 - Yu Wang, Jinchao Li, Tristan Naumann, Chenyan Xiong, Hao Cheng, Robert Tinn, Cliff Wong, Naoto Usuyama, Richard Rogahn, Zhihong Shen, Yang Qin, Eric Horvitz, Paul N. Bennett, Jianfeng Gao, Hoifung Poon:
Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature. 3717-3725 - Zhiwei Wang, Zhengzhang Chen, Jingchao Ni, Hui Liu, Haifeng Chen, Jiliang Tang:
Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection. 3726-3734 - Tongwen Wu, Yu Yang, Yanzhi Li, Huiqiang Mao, Liming Li, Xiaoqing Wang, Yuming Deng:
Representation Learning for Predicting Customer Orders. 3735-3744 - Dongbo Xi, Zhen Chen, Peng Yan, Yinger Zhang, Yongchun Zhu, Fuzhen Zhuang, Yu Chen:
Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising. 3745-3755 - Jianing Xi, Liping Ye, Qinghua Huang, Xuelong Li:
Tolerating Data Missing in Breast Cancer Diagnosis from Clinical Ultrasound Reports via Knowledge Graph Inference. 3756-3764 - Yuan Xia, Chunyu Wang, Zhenhui Shi, Jingbo Zhou, Chao Lu, Haifeng Huang, Hui Xiong:
Medical Entity Relation Verification with Large-scale Machine Reading Comprehension. 3765-3774 - Yikun Xian, Handong Zhao, Tak Yeon Lee, Sungchul Kim, Ryan A. Rossi, Zuohui Fu, Gerard de Melo, S. Muthukrishnan:
EXACTA: Explainable Column Annotation. 3775-3785 - Fengtong Xiao, Lin Li, Weinan Xu, Jingyu Zhao, Xiaofeng Yang, Jun Lang, Hao Wang:
DMBGN: Deep Multi-Behavior Graph Networks for Voucher Redemption Rate Prediction. 3786-3794 - Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou:
FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data. 3795-3805 - Mingzhe Xing, Shuqing Bian, Wayne Xin Zhao, Zhen Xiao, Xingji Luo, Cunxiang Yin, Jing Cai, Yancheng He:
Learning Reliable User Representations from Volatile and Sparse Data to Accurately Predict Customer Lifetime Value. 3806-3816 - Da Xu, Chuanwei Ruan, Evren Körpeoglu, Sushant Kumar, Kannan Achan:
Towards the D-Optimal Online Experiment Design for Recommender Selection. 3817-3825 - Linchuan Xu, Ryo Asaoka, Taichi Kiwaki, Hiroshi Murata, Yuri Fujino, Kenji Yamanishi:
PAMI: A Computational Module for Joint Estimation and Progression Prediction of Glaucoma. 3826-3834 - Nishant Yadav, Rajat Sen, Daniel N. Hill, Arya Mazumdar, Inderjit S. Dhillon:
Session-Aware Query Auto-completion using Extreme Multi-Label Ranking. 3835-3844 - Qian Yang, Jianyi Zhang, Weituo Hao, Gregory P. Spell, Lawrence Carin:
FLOP: Federated Learning on Medical Datasets using Partial Networks. 3845-3853 - Yue Yang, Yuan Shi, Dejian Wang, Qisheng Chen, Lei Xu, Hanqian Li, Zhouyu Fu, Xin Li, Hao Zhang:
Improving the Information Disclosure in Mobility-on-Demand Systems. 3854-3864 - Jiangchao Yao, Feng Wang, Kunyang Jia, Bo Han, Jingren Zhou, Hongxia Yang:
Device-Cloud Collaborative Learning for Recommendation. 3865-3874 - Jaehyuk Yi, Jinkyoo Park:
Semi-supervised Bearing Fault Diagnosis with Adversarially-Trained Phase-Consistent Network. 3875-3885 - Sanshi Yu, Zhuoxuan Jiang, Dongdong Chen, Shanshan Feng, Dongsheng Li, Qi Liu, Jinfeng Yi:
Leveraging Tripartite Interaction Information from Live Stream E-Commerce for Improving Product Recommendation. 3886-3894 - Ningyu Zhang, Qianghuai Jia, Shumin Deng, Xiang Chen, Hongbin Ye, Hui Chen, Huaixiao Tou, Gang Huang, Zhao Wang, Nengwei Hua, Huajun Chen:
AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibaba. 3895-3905 - Qi Zhang, Hengshu Zhu, Ying Sun, Hao Liu, Fuzhen Zhuang, Hui Xiong:
Talent Demand Forecasting with Attentive Neural Sequential Model. 3906-3916 - Qingsong Zhang, Bin Gu, Cheng Deng, Songxiang Gu, Liefeng Bo, Jian Pei, Heng Huang:
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization. 3917-3927 - Wei Zhang, Brendan Kitts, Yanjun Han, Zhengyuan Zhou, Tingyu Mao, Hao He, Shengjun Pan, Aaron Flores, San Gultekin, Tsachy Weissman:
MEOW: A Space-Efficient Nonparametric Bid Shading Algorithm. 3928-3936 - Weijia Zhang, Hao Liu, Lijun Zha, Hengshu Zhu, Ji Liu, Dejing Dou, Hui Xiong:
MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal. 3937-3947 - Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang:
HALO: Hierarchy-aware Fault Localization for Cloud Systems. 3948-3958 - Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang:
AutoLoss: Automated Loss Function Search in Recommendations. 3959-3967 - Yu Zheng, Yongxin Yang, Bowei Chen:
Incorporating Prior Financial Domain Knowledge into Neural Networks for Implied Volatility Surface Prediction. 3968-3975 - Zhipeng Luo, Zhixing He, Jin Wang, Manqing Dong, Jianqiang Huang, Mingjian Chen, Bohang Zheng:
AutoSmart: An Efficient and Automatic Machine Learning Framework for Temporal Relational Data. 3976-3984 - Chang Zhou, Jianxin Ma, Jianwei Zhang, Jingren Zhou, Hongxia Yang:
Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems. 3985-3995 - Tian Zhou, Hao He, Shengjun Pan, Niklas Karlsson, Bharatbhushan Shetty, Brendan Kitts, Djordje Gligorijevic, San Gultekin, Tingyu Mao, Junwei Pan, Jianlong Zhang, Aaron Flores:
An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions. 3996-4004 - Yongchun Zhu, Yudan Liu, Ruobing Xie, Fuzhen Zhuang, Xiaobo Hao, Kaikai Ge, Xu Zhang, Leyu Lin, Juan Cao:
Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising. 4005-4013 - Lixin Zou, Shengqiang Zhang, Hengyi Cai, Dehong Ma, Suqi Cheng, Shuaiqiang Wang, Daiting Shi, Zhicong Cheng, Dawei Yin:
Pre-trained Language Model based Ranking in Baidu Search. 4014-4022
Tutorial Overviews
- Muhammad Aurangzeb Ahmad, Steve Overman, Christine Allen, Vikas Kumar, Ankur Teredesai, Carly Eckert:
Software as a Medical Device: Regulating AI in Healthcare via Responsible AI. 4023-4024 - Cuneyt Gurcan Akcora, Murat Kantarcioglu, Yulia R. Gel:
Data Science on Blockchains. 4025-4026 - Joel Barajas, Narayan Bhamidipati, James G. Shanahan:
Online Advertising Incrementality Testing And Experimentation: Industry Practical Lessons. 4027-4028 - Márcia Barros, Francisco M. Couto, Matilde Pato, Pedro Ruas:
Creating Recommender Systems Datasets in Scientific Fields. 4029-4030 - Laure Berti-Équille, David Dao, Stefano Ermon, Bedharta Goswami:
Challenges in KDD and ML for Sustainable Development. 4031-4032 - Marina Danilevsky, Shipi Dhanorkar, Yunyao Li, Lucian Popa, Kun Qian, Anbang Xu:
Explainability for Natural Language Processing. 4033-4034 - Anupam Datta, Matt Fredrikson, Klas Leino, Kaiji Lu, Shayak Sen, Zifan Wang:
Machine Learning Explainability and Robustness: Connected at the Hip. 4035-4036 - Ian Davidson:
Fairness and Explanation in Clustering and Outlier Detection. 4037 - Boxin Du, Si Zhang, Yuchen Yan, Hanghang Tong:
New Frontiers of Multi-Network Mining: Recent Developments and Future Trend. 4038-4039 - Nitin Gupta, Shashank Mujumdar, Hima Patel, Satoshi Masuda, Naveen Panwar, Sambaran Bandyopadhyay, Sameep Mehta, Shanmukha C. Guttula, Shazia Afzal, Ruhi Sharma Mittal, Vitobha Munigala:
Data Quality for Machine Learning Tasks. 4040-4041 - Alejandro Jaimes, Joel R. Tetreault:
Real-time Event Detection for Emergency Response Tutorial. 4042-4043 - Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu:
Graph Representation Learning: Foundations, Methods, Applications and Systems. 4044-4045 - Jae-Gil Lee, Yuji Roh, Hwanjun Song, Steven Euijong Whang:
Machine Learning Robustness, Fairness, and their Convergence. 4046-4047 - Yaliang Li, Zhen Wang, Bolin Ding, Ce Zhang:
AutoML: A Perspective where Industry Meets Academy. 4048-4049 - Fenglong Ma, Muchao Ye, Junyu Luo, Cao Xiao, Jimeng Sun:
Advances in Mining Heterogeneous Healthcare Data. 4050-4051 - Yu Meng, Jiaxin Huang, Yu Zhang, Jiawei Han:
On the Power of Pre-Trained Text Representations: Models and Applications in Text Mining. 4052-4053 - Preslav Nakov, Giovanni Da San Martino:
Fake News, Disinformation, Propaganda, Media Bias, and Flattening the Curve of the COVID-19 Infodemic. 4054-4055 - Guansong Pang, Charu C. Aggarwal:
Toward Explainable Deep Anomaly Detection. 4056-4057 - Jian Pei, Feida Zhu, Zicun Cong, Xuan Luo, Huiwen Liu, Xin Mu:
Data Pricing and Data Asset Governance in the AI Era. 4058-4059 - Jay Pujara, Pedro A. Szekely, Huan Sun, Muhao Chen:
From Tables to Knowledge: Recent Advances in Table Understanding. 4060-4061 - Jianbin Qin, Wei Wang, Chuan Xiao, Ying Zhang, Yaoshu Wang:
High-Dimensional Similarity Query Processing for Data Science. 4062-4063 - Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Bei Wang:
A Visual Tour of Bias Mitigation Techniques for Word Representations. 4064-4065 - Nihar B. Shah:
KDD 2021 Tutorial on Systemic Challenges and Solutions on Bias and Unfairness in Peer Review. 4066-4067 - Linjun Shou, Ming Gong, Jian Pei, Xiubo Geng, Xingjie Zhou, Daxin Jiang:
Language Scaling: Applications, Challenges and Approaches. 4068-4069 - Brian St. Thomas, Praveen Chandar, Christine Hosey, Fernando Diaz:
Mixed Method Development of Evaluation Metrics. 4070-4071 - Vasilis Syrgkanis, Greg Lewis, Miruna Oprescu, Maggie Hei, Keith Battocchi, Eleanor Dillon, Jing Pan, Yifeng Wu, Paul Lo, Huigang Chen, Totte Harinen, Jeong-Yoon Lee:
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber. 4072-4073 - Jian Tang, Fei Wang, Feixiong Cheng:
Artificial Intelligence for Drug Discovery. 4074-4075 - Truyen Tran, Vuong Le, Hung Le, Thao Minh Le:
From Deep Learning to Deep Reasoning. 4076-4077 - Suresh Venkatasubramanian, Carlos Scheidegger, Sorelle A. Friedler, Aaron Clauset:
Fairness in Networks: Social Capital, Information Access, and Interventions. 4078-4079 - Cong Wang, Xiao-Hui Li, Haocheng Han, Shendi Wang, Luning Wang, Caleb Chen Cao, Lei Chen:
Counterfactual Explanations in Explainable AI: A Tutorial. 4080-4081 - Xin Wang, Wenwu Zhu:
Automated Machine Learning on Graph. 4082-4083 - Lingfei Wu, Yu Chen, Heng Ji, Bang Liu:
Deep Learning on Graphs for Natural Language Processing. 4084-4085 - Han Xu, Yaxin Li, Xiaorui Liu, Wentao Wang, Jiliang Tang:
Adversarial Robustness in Deep Learning: From Practices to Theories. 4086-4087 - Rose Yu, Paris Perdikaris, Anuj Karpatne:
Physics-Guided AI for Large-Scale Spatiotemporal Data. 4088-4089 - Nasser Zalmout, Chenwei Zhang, Xian Li, Yan Liang, Xin Luna Dong:
All You Need to Know to Build a Product Knowledge Graph. 4090-4091 - Chuxu Zhang, Jundong Li, Meng Jiang:
Data Efficient Learning on Graphs. 4092-4093 - Hao Zhang, Zhuohan Li, Lianmin Zheng, Ion Stoica:
Simple and Automatic Distributed Machine Learning on Ray. 4094-4095 - Elena Zheleva, David Arbour:
Causal Inference from Network Data. 4096-4097 - Yong Zheng, David (Xuejun) Wang:
Multi-Objective Recommendations. 4098-4099 - Zirui Zhou, Lingyang Chu, Changxin Liu, Lanjun Wang, Jian Pei, Yong Zhang:
Towards Fair Federated Learning. 4100-4101
Workshop Summaries
- Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan:
Fragile Earth: Accelerating Progress towards Equitable Sustainability. 4102-4103 - Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodríguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash:
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). 4104-4105 - Abraham Bagherjeiran, Nemanja Djuric, Mihajlo Grbovic, Kuang-chih Lee, Kun Liu, Vladan Radosavljevic, Suju Rajan:
AdKDD 2021. 4106-4107 - Siddharth Bhatia, Bryan Hooi, Leman Akoglu, Sourav Chatterjee, Xiaodong Jiang, Manish Gupta:
ODD: Outlier Detection and Description. 4108-4109 - Zeyd Boukhers, Philipp Mayr, Silvio Peroni:
BiblioDAP'21: The 1st Workshop on Bibliographic Data Analysis and Processing. 4110-4111 - Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu:
Third Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2021). 4112-4113 - Nicolas Chopin, Mike Gartrell, Dawen Liang, Alberto Lumbreras, David Rohde, Yixin Wang:
Bayesian Causal Inference for Real World Interactive Systems. 4114-4115 - Xiquan Cui, Estelle Afshar, Khalifeh Al Jadda, Srijan Kumar, Julian J. McAuley, Tao Ye, Kamelia Aryafar, Vachik S. Dave, Mohammad Korayem:
Workshop on Online and Adaptative Recommender Systems (OARS). 4116-4117 - Sunipa Dev, Mehrnoosh Sameki, Jwala Dhamala, Cho-Jui Hsieh:
Measures and Best Practices for Responsible AI. 4118 - Ming Ding, Yuxiao Dong, Xiao Liu, Jiezhong Qiu, Jie Tang, Zhilin Yang:
The International Workshop on Pretraining: Algorithms, Architectures, and Applications ([email protected] 2021). 4119-4120 - Ying Ding, Bogdan G. Arsintescu, Ching-Hua Chen, Haoyun Feng, François Scharffe, Oshani Seneviratne, Juan Sequeda:
International Workshop on Knowledge Graph: Heterogenous Graph Deep Learning and Applications. 4121-4122 - Eduard C. Dragut, Yunyao Li, Lucian Popa, Slobodan Vucetic:
Data Science with Human in the Loop. 4123-4124 - Snehalkumar (Neil) S. Gaikwad, Shankar Iyer, Dalton D. Lunga, Elizabeth Bondi:
Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning. 4125-4126 - Benjamin Han, Douglas Burdick, Dave Lewis, Yijuan Lu, Hamid Motahari, Sandeep Tata:
DI-2021: The Second Document Intelligence Workshop. 4127-4128 - Aude Hofleitner, Meng Jiang, Srijan Kumar, Neil Shah, Kai Shu:
The Second International MIS2 Workshop: Misinformation and Misbehavior Mining on the Web. 4129-4130 - Estevam Hruschka, Tom M. Mitchell, Marko Grobelnik, Behzad Golshan:
WIT: Workshop on deriving Insights from user-generated Text. 4131-4132 - Daniel R. Jiang, Haipeng Luo, Chu Wang, Yingfei Wang:
Multi-Armed Bandits and Reinforcement Learning: Advancing Decision Making in E-Commerce and Beyond. 4133-4134 - Sumeet Katariya, Nikhil Rao, Chandan K. Reddy:
Workshop on Data-Efficient Machine Learning (DeMaL). 4135-4136 - ChanGhee Koh, SoYoung Kim, Nathaniel Tan:
2021 KDD Workshop on Understanding Public Perceptions for Applied Data Science: How Important is it to Engage Society in Technology Development? 4137-4138 - Senthil Kumar, Leman Akoglu, Nitesh V. Chawla, José A. Rodríguez-Serrano, Tanveer A. Faruquie, Saurabh Nagrecha:
Machine Learning in Finance. 4139-4140 - Thuc Duy Le, Jiuyong Li, Gregory Cooper, Sofia Triantafillou, Elias Bareinboim, Huan Liu, Negar Kiyavash:
The KDD 2021 Workshop on Causal Discovery (CD2021). 4141-4142 - Subhabrata Mukherjee, Qi Li, Sihong Xie, Philip S. Yu, Jing Gao:
The Third International TrueFact Workshop: Making a Credible Web for Tomorrow. 4143-4144 - Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich:
Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA). 4145-4146 - Hima Patel, Fuyuki Ishikawa, Laure Berti-Équille, Nitin Gupta, Sameep Mehta, Satoshi Masuda, Shashank Mujumdar, Shazia Afzal, Srikanta Bedathur, Yasuharu Nishi:
2nd International Workshop on Data Quality Assessment for Machine Learning. 4147-4148 - Claudia Plant, Alvitta Ottley, Liang Gou, Torsten Möller, Adam Perer, Alexander Lex, Junming Shao:
VDS'21: Visualization in Data Science. 4149-4150 - Sanjay Purushotham, Yaguang Li, Zhengping Che:
MiLeTS'21: 7th KDD Workshop on Mining and Learning from Time Series. 4151-4152 - Sagar Samtani, Shanchieh Yang, Hsinchun Chen:
ACM KDD AI4Cyber: The 1st Workshop on Artificial Intelligence-enabled Cybersecurity Analytics. 4153-4154 - Toryn L. J. Schafer, Ryan M. McGranaghan, Mila Getmansky Sherman, Mei-Ling E. Feng, Olukunle O. Owolabi, Sean E. Ryan, Marie-Christine Düker, Michael Jauch, David S. Matteson:
Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research. 4155-4156 - Chuan Shi, Yuan Fang, Yanfang Ye, Jiawei Zhang:
The 4th Workshop on Heterogeneous Information Network Analysis and Applications (HENA 2021). 4157-4158 - Fei Wang, Prithwish Chakraborty, Tao Xu, Pei-Yun Sabrina Hsueh, Xudong Sun, Gregor Stiglic, Gracy Crane, Jiang Bian, Laleh Haghverdi, Lixia Yao, Florian Buettner:
KDD Health Day/DSHealth 2021: Joint KDD 2021 Health Day and 2021 KDD Workshop on Applied Data Science for Healthcare: State of XAI and Trustworthiness in Health. 4159-4160 - Gang Wang, Arridhana Ciptadi, Ali Ahmadzadeh:
MLHat: Deployable Machine Learning for Security Defense. 4161-4162 - Tao Wang, Patrick Koch, Brett Wujek, Jun Liu, Hai Li:
The Fifth International Workshop on Automation in Machine Learning. 4163-4164 - Wen Wang, Han Zhao, Dokyun Lee, George H. Chen:
Machine Learning for Consumers and Markets. 4165-4166 - Lingfei Wu, Jiliang Tang, Yinglong Xia, Jian Pei, Xiaojie Guo:
The Sixth International Workshop on Deep Learning on Graphs - Methods and Applications (DLG-KDD'21). 4167-4168 - Hui Xiong, Hengshu Zhu, Tong Xu, Xi Zhang:
TMC 2021: 2021 International Workshop on Talent and Management Computing. 4169-4170 - Chang Xu, Siqi Ma, David Lo:
PLP 2021: Workshop on Programming Language Processing. 4171-4172 - Jianpeng Xu, Lingfei Wu, Xiaolin Pang, Mohit Sharma, Dawei Yin, George Karypis, Justin Basilico, Philip S. Yu:
2nd International Workshop on Industrial Recommendation Systems (IRS). 4173-4174 - Da Yan, Steve Qin, Debswapna Bhattacharya, Jake Y. Chen, Mohammed J. Zaki:
20th International Workshop on Data Mining in Bioinformatics (BIOKDD 2021). 4175-4176 - Shan You, Chang Xu, Fei Wang, Changshui Zhang:
Workshop on Model Mining. 4177-4178 - Jian Zhang, Jian Tang, Yiran Chen, Jie Liu, Jieping Ye, Marilyn Wolf, Vijaykrishnan Narayanan, Mani Srivastava, Michael I. Jordan, Victor Bahl:
The 4th Artificial Intelligence of Things (AIoT) Workshop. 4179-4180 - Guanjie Zheng, Porter Jenkins, Yanyan Xu, Dongyao Chen:
Overview of the 1st Workshop on City Brain Research. 4181-4182 - Xun Zhou, Liang Zhao, Zhe Jiang, Robert N. Stewart, Shashi Shekhar, Jieping Ye:
DeepSpatial'21: 2nd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems. 4183-4184 - Feida Zhu, Jian Pei:
The Third International Workshop on Smart Data for Blockchain and Distributed Ledger (SDBD2021): Joint Workshop with SIGKDD 2021 Trust Day. 4185-4186 - Xiaoqiang Zhu, Kuang-chih Lee, Guorui Zhou, Biye Jiang, Zhe Wang, Ruiming Tang, Kan Ren, Qingyao Ai, Weinan Zhang:
3rd International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2021. 4187-4188
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