| 2021 | ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting. | Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang |
| 2021 | MiniRocket: A Very Fast (Almost) Deterministic Transform for Time Series Classification. | Angus Dempster, Daniel F. Schmidt, Geoffrey I. Webb |
| 2021 | PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics. | Arka Daw, M. Maruf, Anuj Karpatne |
| 2021 | Fairness and Explanation in Clustering and Outlier Detection. | Ian Davidson |
| 2021 | Machine Learning Explainability and Robustness: Connected at the Hip. | Anupam Datta, Matt Fredrikson, Klas Leino, Kaiji Lu, Shayak Sen, Zifan Wang |
| 2021 | Explainability for Natural Language Processing. | Marina Danilevsky, Shipi Dhanorkar, Yunyao Li, Lucian Popa, Kun Qian, Anbang Xu |
| 2021 | Labeled Data Generation with Inexact Supervision. | Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang |
| 2021 | NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. | Enyan Dai, Charu Aggarwal, Suhang Wang |
| 2021 | Would Your Tweet Invoke Hate on the Fly? Forecasting Hate Intensity of Reply Threads on Twitter. | Snehil Dahiya, Shalini Sharma, Dhruv Sahnan, Vasu Goel, Emilie Chouzenoux, Vctor Elvira, Angshul Majumdar, Anil Bandhakavi, Tanmoy Chakraborty |
| 2021 | Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility. | Sen Cui, Weishen Pan, Changshui Zhang, Fei Wang |
| 2021 | Workshop on Online and Adaptative Recommender Systems (OARS). | Xiquan Cui, Estelle Afshar, Khalifeh Al Jadda, Srijan Kumar, Julian J. McAuley, Tao Ye, Kamelia Aryafar, Vachik S. Dave, Mohammad Korayem |
| 2021 | Bavarian: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages. | Cyrus Cousins, Chloe Wohlgemuth, Matteo Riondato |
| 2021 | Graph Similarity Description: How Are These Graphs Similar? | Corinna Coupette, Jilles Vreeken |
| 2021 | Theory meets Practice at the Median: A Worst Case Comparison of Relative Error Quantile Algorithms. | Graham Cormode, Abhinav Mishra, Joseph Ross, Pavel Vesel |
| 2021 | Automated Mechanism Design for Strategic Classification: Abstract for KDD'21 Keynote Talk. | Vincent Conitzer |
| 2021 | Improve Learning from Crowds via Generative Augmentation. | Zhendong Chu, Hongning Wang |
| 2021 | Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data. | Zhixuan Chu, Stephen L. Rathbun, Sheng Li |
| 2021 | Robust Object Detection Fusion Against Deception. | Ka-Ho Chow, Ling Liu |
| 2021 | FASER: Seismic Phase Identifier for Automated Monitoring. | Farhan Asif Chowdhury, M. Ashraf Siddiquee, Glenn Eli Baker, Abdullah Mueen |
| 2021 | Bayesian Causal Inference for Real World Interactive Systems. | Nicolas Chopin, Mike Gartrell, Dawen Liang, Alberto Lumbreras, David Rohde, Yixin Wang |
| 2021 | Interpreting Internal Activation Patterns in Deep Temporal Neural Networks by Finding Prototypes. | Sohee Cho, Wonjoon Chang, Ginkyeng Lee, Jaesik Choi |
| 2021 | Learning Elastic Embeddings for Customizing On-Device Recommenders. | Tong Chen, Hongzhi Yin, Yujia Zheng, Zi Huang, Yang Wang, Meng Wang |
| 2021 | Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction. | 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 |
| 2021 | PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks. | Junjie Chen, Wendy Hui Wang, Hongchang Gao, Xinghua Shi |
| 2021 | Graph Deep Factors for Forecasting with Applications to Cloud Resource Allocation. | Hongjie Chen, Ryan A. Rossi, Kanak Mahadik, Sungchul Kim, Hoda Eldardiry |