Weiran Huang

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 49

Top Topics

Rank Correlation

Influence Maximization

Top Venues

Publications

Lai Wei, Zhiquan Tan, Chenghai Li, Jindong Wang, Weiran Huang
Large Language Model Evaluation via Matrix Entropy. CoRR (2024)
Kun Song, Zhiquan Tan, Bochao Zou, Huimin Ma, Weiran Huang
Unveiling the Dynamics of Information Interplay in Supervised Learning. CoRR (2024)
Yichen Wen, Zhiquan Tan, Kaipeng Zheng, Chuanlong Xie, Weiran Huang
Provable Contrastive Continual Learning. CoRR (2024)
Xuyang Zhao, Huiyuan Wang, Weiran Huang, Wei Lin
A Statistical Theory of Regularization-Based Continual Learning. CoRR (2024)
Zhiquan Tan, Chenghai Li, Weiran Huang
The Information of Large Language Model Geometry. CoRR (2024)
Zhiquan Tan, Lai Wei, Jindong Wang, Xing Xie, Weiran Huang
Can I understand what I create? Self-Knowledge Evaluation of Large Language Models. CoRR (2024)
Xuyang Zhao, Tianqi Du, Yisen Wang, Jun Yao, Weiran Huang
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations. CoRR (2023)
Zihao Jiang, Yunkai Dang, Dong Pang, Huishuai Zhang, Weiran Huang
FILM: How can Few-Shot Image Classification Benefit from Pre-Trained Language Models? CoRR (2023)
Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. ICLR (2023)
Xiuyuan Chen, Yuan Lin, Yuchen Zhang, Weiran Huang
AutoEval-Video: An Automatic Benchmark for Assessing Large Vision Language Models in Open-Ended Video Question Answering. CoRR (2023)
Kaipeng Zheng, Weiran Huang, Lichao Sun
Efficient Few-Shot Clinical Task Adaptation with Large Language Models. CoRR (2023)
Lai Wei, Zihao Jiang, Weiran Huang, Lichao Sun
InstructionGPT-4: A 200-Instruction Paradigm for Fine-Tuning MiniGPT-4. CoRR (2023)
Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan, Yifan Zhang
Information Flow in Self-Supervised Learning. CoRR (2023)
Kun Song, Huimin Ma, Bochao Zou, Huishuai Zhang, Weiran Huang
FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning. NeurIPS (2023)
Manyi Zhang, Xuyang Zhao, Jun Yao, Chun Yuan, Weiran Huang
When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method. ICCV (2023)
Kaipeng Zheng, Huishuai Zhang, Weiran Huang
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation. CoRR (2023)
Zhiquan Tan, Weiran Huang
Understanding Grokking Through A Robustness Viewpoint. CoRR (2023)
Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang
Rethinking Weak Supervision in Helping Contrastive Learning. CoRR (2023)
Kaipeng Zheng, Huishuai Zhang, Weiran Huang
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation. NeurIPS (2023)
Xuyang Zhao, Tianqi Du, Yisen Wang, Jun Yao, Weiran Huang
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations. ICLR (2023)
Kun Song, Huimin Ma, Bochao Zou, Huishuai Zhang, Weiran Huang
FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning. CoRR (2023)
Zhiquan Tan, Kaipeng Zheng, Weiran Huang
OTMatch: Improving Semi-Supervised Learning with Optimal Transport. CoRR (2023)
Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang
Rethinking Weak Supervision in Helping Contrastive Learning. ICML (2023)
Weiran Huang, Mingyang Yi, Xuyang Zhao, Zihao Jiang
Towards the Generalization of Contrastive Self-Supervised Learning. ICLR (2023)
Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. CoRR (2022)
Jiaye Teng, Weiran Huang, Haowei He
Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis. AISTATS (2022)
Manyi Zhang, Chun Yuan, Jun Yao, Weiran Huang
Learning with Noisily-labeled Class-imbalanced Data. CoRR (2022)
Jiaye Teng, Weiran Huang
Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis. CoRR (2021)
Weiran Huang, Mingyang Yi, Xuyang Zhao
Towards the Generalization of Contrastive Self-Supervised Learning. CoRR (2021)
Jiacheng Sun, Xiangyong Cao, Hanwen Liang, Weiran Huang, Zewei Chen, Zhenguo Li
New Interpretations of Normalization Methods in Deep Learning. AAAI (2020)
Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang
Locally Differentially Private (Contextual) Bandits Learning. CoRR (2020)
Jiacheng Sun, Xiangyong Cao, Hanwen Liang, Weiran Huang, Zewei Chen, Zhenguo Li
New Interpretations of Normalization Methods in Deep Learning. CoRR (2020)
Yimin Huang, Weiran Huang, Liang Li, Zhenguo Li
Meta-Learning PAC-Bayes Priors in Model Averaging. AAAI (2020)
Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang
Boosting Few-Shot Learning With Adaptive Margin Loss. CoRR (2020)
Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang
Boosting Few-Shot Learning With Adaptive Margin Loss. CVPR (2020)
Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang
Locally Differentially Private (Contextual) Bandits Learning. NeurIPS (2020)
Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu
Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks. AAAI (2019)
Aoxue Li, Tiange Luo, Tao Xiang, Weiran Huang, Liwei Wang
Few-Shot Learning With Global Class Representations. ICCV (2019)
Tiange Luo, Aoxue Li, Tao Xiang, Weiran Huang, Liwei Wang
Few-Shot Learning with Global Class Representations. CoRR (2019)
Hanwen Liang, Shifeng Zhang, Jiacheng Sun, Xingqiu He, Weiran Huang, Kechen Zhuang, Zhenguo Li
DARTS+: Improved Differentiable Architecture Search with Early Stopping. CoRR (2019)
Yimin Huang, Weiran Huang, Liang Li, Zhenguo Li
Meta-Learning PAC-Bayes Priors in Model Averaging. CoRR (2019)
Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu
Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks. CoRR (2018)
Xiaowei Chen, Weiran Huang, Wei Chen, John C. S. Lui
Community Exploration: From Offline Optimization to Online Learning. NeurIPS (2018)
Lichao Sun, Weiran Huang, Philip S. Yu, Wei Chen
Multi-Round Influence Maximization (Extended Version). CoRR (2018)
Weiran Huang, Jungseul Ok, Liang Li, Wei Chen
Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications (Extended Version). CoRR (2018)
Xiaowei Chen, Weiran Huang, Wei Chen, John C. S. Lui
Community Exploration: From Offline Optimization to Online Learning. CoRR (2018)
Weiran Huang, Jungseul Ok, Liang Li, Wei Chen
Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications. IJCAI (2018)
Lichao Sun, Weiran Huang, Philip S. Yu, Wei Chen
Multi-Round Influence Maximization. KDD (2018)
Weiran Huang, Liang Li, Wei Chen
Partitioned Sampling of Public Opinions Based on Their Social Dynamics. AAAI (2017)
Weiran Huang, Liang Li, Wei Chen
Partitioned Sampling of Public Opinions Based on Their Social Evolution. CoRR (2015)