1 | Part-dependent Label Noise: Towards Instance-dependent Label Noise | Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama | Pattern Recognition, Computer Science, Artificial Intelligence |

2 | Causal Intervention for Weakly-Supervised Semantic Segmentation. | Dong Zhang, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun | Segmentation, Natural Language Processing, Computer Science, Artificial Intelligence |

3 | Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect | Kaihua Tang, Jianqiang Huang, Hanwang Zhang | Momentum, Econometrics, Mathematics, Form Of The Good, Causal Effect |

4 | Interventional Few-Shot Learning | Zhongqi Yue, Hanwang Zhang, Qianru Sun, Xian-Sheng Hua | Medical Physics, Computer Science |

5 | Provably Consistent Partial-Label Learning | Lei Feng, Jiaqi Lv, Bo Han, Miao Xu, Gang Niu, Xin Geng, Bo An, Masashi Sugiyama | Theoretical Computer Science, Computer Science |

6 | Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning | Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama | Stochastic Matrix, Algorithm, Mathematics |

7 | Watch out! Motion is Blurring the Vision of Your Deep Neural Networks | Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Jian Wang, Bing Yu, Wei Feng, Yang Liu | Computer Vision, Computer Science, Artificial Intelligence, Deep Neural Networks |

8 | Federated Bayesian Optimization via Thompson Sampling | Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet | Bayesian Optimization, Thompson Sampling, Machine Learning, Computer Science, Artificial Intelligence |

9 | Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning | Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin | Knowledge Management, Computer Science, Continual Learning |

10 | Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning | Cong Zhang, Wen Song, Zhiguang Cao, Jie Zhang, Puay Siew Tan, Xu Chi | Job Shop Scheduling, Reinforcement Learning, Operations Research, Computer Science |

11 | The route to chaos in routing games: When is price of anarchy too optimistic? | Thiparat Chotibut, Fryderyk Falniowski, Michał Misiurewicz, Georgios Piliouras | Price Of Anarchy, Mathematical Economics, Economics |

12 | Neural Sparse Voxel Fields | Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, Christian Theobalt | Voxel, Pattern Recognition, Computer Science, Artificial Intelligence |

13 | Synthesizing Tasks for Block-based Programming | Umair Z. Ahmed, Maria Christakis, Aleksandr Efremov, Nigel Fernandez, Ahana Ghosh, Abhik Roychoudhury, Adish Singla | Programming Language, Computer Science |

14 | Variational Bayesian Unlearning | Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet | Bayesian Probability, Artificial Intelligence |

15 | Theory-Inspired Path-Regularized Differential Network Architecture Search | Pan Zhou, Caiming Xiong, Richard Socher, Steven Chu Hong Hoi | Network Architecture, Artificial Intelligence, Computer Science |

16 | Rethinking Importance Weighting for Deep Learning under Distribution Shift | Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama | Weighting, Deep Learning, Machine Learning, Computer Science, Artificial Intelligence |

17 | ConvBERT: Improving BERT with Span-based Dynamic Convolution | Zi-Hang Jiang, Weihao Yu, Daquan Zhou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan | Convolution, Algorithm, Computer Science |

18 | Neural encoding with visual attention | Meenakshi Khosla, Gia H. Ngo, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu | Encoding, Speech Recognition, Computer Science, Visual Attention |

19 | Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games | Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang | Reinforcement Learning, Artificial Intelligence, Computer Science |

20 | MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. | Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang | Mesa, Data Mining, Computer Science |

21 | Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev | Xiao Wang, Qi Lei, Ioannis Panageas | Langevin Dynamics, Sobolev Space, Geodesic, Manifold, Convergence, Mathematical Analysis, Mathematics |

22 | Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent | Dimitris Fotakis, Thanasis Lianeas, Georgios Piliouras, Stratis Skoulakis | Gradient Descent, Dimensionality Reduction, Mathematical Optimization, Computer Science, Online Learning |

23 | On Testing of Samplers | Kuldeep S Meel, Yash Pralhad Pote, Sourav Chakraborty | |

24 | Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples | Jay Nandy, Wynne Hsu, Mong Li Lee | Mathematical Optimization, Computer Science |

25 | No-Regret Learning and Mixed Nash Equilibria: They Do Not Mix | Emmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Thanasis Lianeas, Panayotis Mertikopoulos, Georgios Piliouras | Regret, Nash Equilibrium, Mathematical Economics, Economics |

26 | Optimal Query Complexity of Secure Stochastic Convex Optimization | Wei Tang, Chien-Ju Ho, Yang Liu | Convex Optimization, Mathematical Optimization, Computer Science |

27 | Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization | Haoliang Li, Yufei Wang, Renjie Wan, Shiqi Wang, Tie-Qiang Li, Alex C. Kot | Medical Imaging, Regularization, Pattern Recognition, Computer Science, Artificial Intelligence, Linear Dependency |

28 | Cross-Scale Internal Graph Neural Network for Image Super-Resolution | Shangchen Zhou, Jiawei Zhang, Wangmeng Zuo, Chen Change Loy | Algorithm, Computer Science, Cross Scale, Graph Neural Networks, Superresolution |

29 | Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation | Jianyuan Wang, Yiran Zhong, Yuchao Dai, Kaihao Zhang, Pan Ji, Hongdong Li | Invariant, Algorithm, Computer Science, Optical Flow Estimation |

30 | Inference Stage Optimization for Cross-scenario 3D Human Pose Estimation | Jianfeng Zhang, Xuecheng Nie, Jiashi Feng | Inference, Pose, Machine Learning, Computer Science, Artificial Intelligence |

31 | Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning | Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S Meel, N. V. Vinodchandran | Mathematical Analysis, Mathematics, Distance Approximation, High Dimensional |

32 | The Generalized Lasso with Nonlinear Observations and Generative Priors | Zhaoqiang Liu, Jonathan Scarlett | Lasso, Prior Probability, Nonlinear System, Generative Grammar, Algorithm, Computer Science |

33 | Improving Generalization in Reinforcement Learning with Mixture Regularization | Kaixin Wang, Bingyi Kang, Jie Shao, Jiashi Feng | Reinforcement Learning, Regularization, Artificial Intelligence, Computer Science |

34 | Correlation Robust Influence Maximization | Louis Chen, Divya Padmanabhan, Chee Chin Lim, Karthik Natarajan | Maximization, Correlation, Mathematical Optimization, Mathematics |

35 | Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization | Sreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low, Harold Soh | Bayesian Optimization, Artificial Intelligence, Computer Science, Inverse Reinforcement Learning |

36 | Taming Discrete Integration via the Boon of Dimensionality | Jeffrey M. Dudek, Dror Fried, Kuldeep S. Meel | Curse Of Dimensionality, Theoretical Computer Science, Computer Science |

37 | Digraph Inception Convolutional Networks | Zekun Tong, Yuxuan Liang, Changsheng Sun, Xinke Li, David Rosenblum, Andrew Lim | Digraph, Discrete Mathematics, Computer Science |

38 | Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep Learning | Pan Zhou, Jiashi Feng, Chao Ma, Caiming Xiong, Steven Chu Hong Hoi, Weinan E | Deep Learning, Cognitive Science, Computer Science, Artificial Intelligence |

39 | Balanced Meta-Softmax for Long-Tailed Visual Recognition | Ren Jiawei, Cunjun Yu, shunan sheng, Xiao Ma, Haiyu Zhao, Shuai Yi, hongsheng Li | Softmax Function, Speech Recognition, Computer Science, Visual Recognition |

40 | Chaos, Extremism and Optimism: Volume Analysis of Learning in Games | Yun Kuen Cheung, Georgios Piliouras | Optimism, Social Psychology, Psychology, Volume Analysis |

41 | Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting | Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Congrui Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang | Time Series, Multivariate Statistics, Pattern Recognition, Computer Science, Artificial Intelligence, Graph Neural Networks |

42 | Storage Efficient and Dynamic Flexible Runtime Channel Pruning via Deep Reinforcement Learning | Jianda Chen, Shangyu Chen, Sinno Jialin Pan | Reinforcement Learning, Channel, Pruning, Distributed Computing, Computer Science |

43 | Self-Supervised Relationship Probing | Jiuxiang Gu, Jason Kuen, Shafiq Joty, Jianfei Cai, Vlad Morariu, Handong Zhao, Tong Sun | Machine Learning, Psychology, Artificial Intelligence |

44 | Partially View-aligned Clustering | Zhenyu Huang, Peng Hu, Joey Tianyi Zhou, Jiancheng Lv, Xi Peng | Cluster Analysis, Pattern Recognition, Computer Science, Artificial Intelligence |