Publications

*: Equal contribution or alphabetic ordering.
†: Corresponding author.

Conference Papers

• Towards the Generalization of Contrastive Self-Supervised Learning.
  Weiran Huang*†, Mingyang Yi*, Xuyang Zhao*, Zihao Jiang.
  International Conference on Learning Representations (ICLR), 2023.
  [code] [slides] [知乎]

• Towards the Out-of-Distribution Generalization of Contrastive Self-Supervised Learning.
  Xuyang Zhao*, Tianqi Du*, Yisen Wang, Jun Yao, Weiran Huang†.
  International Conference on Learning Representations (ICLR), 2023.

• Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding.
  Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang†.
  International Conference on Learning Representations (ICLR), 2023.

• AggNCE: Asymptotically Identifiable Contrastive Learning. (Oral Presentation)
  Jingyi Cui*, Weiran Huang*, Yifei Wang, Yisen Wang.
  NeurIPS 2022 Workshop on Self-Supervised Learning Theory and Practice (NeurIPS Workshop), 2022.
  [video]

• Variational Energy-Based Models: A Probabilistic Framework for Contrastive Self-Supervised Learning.
  Tianqi Du*, Yifei Wang*, Weiran Huang, Yisen Wang.
  NeurIPS 2022 Workshop on Self-Supervised Learning Theory and Practice (NeurIPS Workshop), 2022.

• Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis.
  Jiaye Teng*, Weiran Huang*†, Haowei He*.
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2022.
  [slides] [poster] [video] [知乎]

• Locally Differentially Private (Contextual) Bandits Learning.
  Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang.
  Conference on Neural Information Processing Systems (NeurIPS), 2020.
  [code] [slides] [知乎]

• Boosting Few-Shot Learning With Adaptive Margin Loss.
  Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
  [slides] [patent] [知乎]

• Meta-Learning Pac-Bayes Priors in Model Averaging.
  Yimin Huang, Weiran Huang, Liang Li, Zhenguo Li.
  AAAI Conference on Artificial Intelligence (AAAI), 2020.

• New Interpretations of Normalization Methods in Deep Learning.
  Jiacheng Sun, Xiangyong Cao, Hanwen Liang, Weiran Huang, Zewei Chen, Zhenguo Li.
  AAAI Conference on Artificial Intelligence (AAAI), 2020.

• Few-Shot Learning With Global Class Representations.
  Aoxue Li, Tiange Luo, Tao Xiang, Weiran Huang, Liwei Wang.
  International Conference on Computer Vision (ICCV), 2019.
  [code] [poster] [patent] [知乎]

• Modeling Local Dependence in Natural Language With Multi-Channel Recurrent Neural Networks. (Oral Presentation)
  Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu.
  AAAI Conference on Artificial Intelligence (AAAI), 2019.

• Community Exploration: From Offline Optimization to Online Learning.
  Xiaowei Chen, Weiran Huang, Wei Chen, John C.S. Lui.
  Conference on Neural Information Processing Systems (NeurIPS), 2018.
  [poster]

• Multi-Round Influence Maximization. (Long Presentation)
  Lichao Sun, Weiran Huang, Philip S. Yu, Wei Chen.
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2018.

• Combinatorial Pure Exploration With Continuous and Separable Reward Functions and Its Applications.
  Weiran Huang, Jungseul Ok, Liang Li, Wei Chen.
  International Joint Conference on Artificial Intelligence (IJCAI), 2018.
  [slides]

• Partitioned Sampling of Public Opinions Based on Their Social Dynamics.
  Weiran Huang, Liang Li, Wei Chen.
  AAAI Conference on Artificial Intelligence (AAAI), 2017.
  [poster]

Preprints and Manuscripts

• Learning With Noisily-Labeled Class-Imbalanced Data.
  Manyi Zhang, Chun Yuan, Jun Yao, Weiran Huang.

• DARTS+: Improved Differentiable Architecture Search With Early Stopping.
  Hanwen Liang, Shifeng Zhang, Jiacheng Sun, Xingqiu He, Weiran Huang, Kechen Zhuang, Zhenguo Li.
  [知乎]