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ORCIDWeiran Huang 0001
Person information
- unicode name: 黄维然
- affiliation: Shanghai Jiao Tong University, China
- affiliation (former): Noah's Ark Lab
- affiliation (former): Tsinghua University, China
Other persons with the same name
- Weiran Huang 0002 — Chinese University of Hong Kong, Hong Kong
- Wei-Ran Huang 0003 (aka: Weiran Huang 0003) — University of Science and Technology of China, Department of Chemistry, Hefei, China
- Weiran Huang 0004 — Peking University Health Science Center, School of Pharmaceutical Sciences, China
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2020 – today
- 2024
[c24]Kun Song, Zhiquan Tan, Bochao Zou, Huimin Ma, Weiran Huang:
Unveiling the Dynamics of Information Interplay in Supervised Learning. ICML 2024- [c23]Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan, Yifan Zhang:
Information Flow in Self-Supervised Learning. ICML 2024 - [c22]Zhiquan Tan, Kaipeng Zheng, Weiran Huang:
OTMatch: Improving Semi-Supervised Learning with Optimal Transport. ICML 2024 - [c21]Yichen Wen, Zhiquan Tan, Kaipeng Zheng, Chuanlong Xie, Weiran Huang:
Provable Contrastive Continual Learning. ICML 2024 - [c20]Yifan Zhang, Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan:
Matrix Information Theory for Self-Supervised Learning. ICML 2024 - [c19]Xuyang Zhao, Huiyuan Wang, Weiran Huang, Wei Lin:
A Statistical Theory of Regularization-Based Continual Learning. ICML 2024 - [i36]Lai Wei, Zhiquan Tan, Chenghai Li, Jindong Wang, Weiran Huang:
Large Language Model Evaluation via Matrix Entropy. CoRR abs/2401.17139 (2024) - [i35]Zhiquan Tan, Chenghai Li, Weiran Huang:
The Information of Large Language Model Geometry. CoRR abs/2402.03471 (2024) - [i34]Di Zhang, Wei Liu, Qian Tan, Jingdan Chen, Hang Yan, Yuliang Yan, Jiatong Li, Weiran Huang, Xiangyu Yue, Dongzhan Zhou, Shufei Zhang, Mao Su, Hansen Zhong, Yuqiang Li, Wanli Ouyang:
ChemLLM: A Chemical Large Language Model. CoRR abs/2402.06852 (2024) - [i33]Kang Zhang, Osamu Yoshie, Weiran Huang:
BreakGPT: A Large Language Model with Multi-stage Structure for Financial Breakout Detection. CoRR abs/2402.07536 (2024) - [i32]Yichen Wen, Zhiquan Tan, Kaipeng Zheng, Chuanlong Xie, Weiran Huang:
Provable Contrastive Continual Learning. CoRR abs/2405.18756 (2024) - [i31]Kun Song, Zhiquan Tan, Bochao Zou, Huimin Ma, Weiran Huang:
Unveiling the Dynamics of Information Interplay in Supervised Learning. CoRR abs/2406.03999 (2024) - [i30]Zhiquan Tan, Lai Wei, Jindong Wang, Xing Xie, Weiran Huang:
Can I understand what I create? Self-Knowledge Evaluation of Large Language Models. CoRR abs/2406.06140 (2024) - [i29]Xuyang Zhao, Huiyuan Wang, Weiran Huang, Wei Lin:
A Statistical Theory of Regularization-Based Continual Learning. CoRR abs/2406.06213 (2024) - [i28]Lai Wei, Zhen Ying, Muyang He, Yutong Chen, Qian Yang, Yanzhe Hong, Jiaping Lu, Xiaoying Li, Weiran Huang, Ying Chen:
An adapted large language model facilitates multiple medical tasks in diabetes care. CoRR abs/2409.13191 (2024) - [i27]Kun Song, Zhiquan Tan, Bochao Zou, Jiansheng Chen, Huimin Ma, Weiran Huang:
Exploring Information-Theoretic Metrics Associated with Neural Collapse in Supervised Training. CoRR abs/2409.16767 (2024) - 2023
- [c18]Manyi Zhang, Xuyang Zhao, Jun Yao, Chun Yuan, Weiran Huang:
When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method. ICCV 2023: 15844-15854 - [c17]Weiran Huang, Mingyang Yi, Xuyang Zhao, Zihao Jiang:
Towards the Generalization of Contrastive Self-Supervised Learning. ICLR 2023 - [c16]Tianyang Hu, Zhili Liu, Fengwei Zhou
, Wenjia Wang, Weiran Huang:
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. ICLR 2023 - [c15]Xuyang Zhao, Tianqi Du, Yisen Wang, Jun Yao, Weiran Huang:
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations. ICLR 2023 - [c14]Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang:
Rethinking Weak Supervision in Helping Contrastive Learning. ICML 2023: 6448-6467 - [c13]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 - [c12]Kaipeng Zheng, Huishuai Zhang, Weiran Huang:
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation. NeurIPS 2023 - [i26]Xuyang Zhao, Tianqi Du, Yisen Wang, Jun Yao, Weiran Huang:
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations. CoRR abs/2303.01092 (2023) - [i25]Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang:
Rethinking Weak Supervision in Helping Contrastive Learning. CoRR abs/2306.04160 (2023) - [i24]Zihao Jiang, Yunkai Dang, Dong Pang, Huishuai Zhang, Weiran Huang:
FILM: How can Few-Shot Image Classification Benefit from Pre-Trained Language Models? CoRR abs/2307.04114 (2023) - [i23]Kaipeng Zheng, Huishuai Zhang, Weiran Huang:
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation. CoRR abs/2307.15317 (2023) - [i22]Lai Wei, Zihao Jiang, Weiran Huang, Lichao Sun:
InstructionGPT-4: A 200-Instruction Paradigm for Fine-Tuning MiniGPT-4. CoRR abs/2308.12067 (2023) - [i21]Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan, Yifan Zhang:
Information Flow in Self-Supervised Learning. CoRR abs/2309.17281 (2023) - [i20]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 abs/2310.15105 (2023) - [i19]Zhiquan Tan, Kaipeng Zheng, Weiran Huang:
OTMatch: Improving Semi-Supervised Learning with Optimal Transport. CoRR abs/2310.17455 (2023) - [i18]Zhiquan Tan, Weiran Huang:
Understanding Grokking Through A Robustness Viewpoint. CoRR abs/2311.06597 (2023) - [i17]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 abs/2311.14906 (2023) - [i16]Kaipeng Zheng, Weiran Huang, Lichao Sun:
Efficient Few-Shot Clinical Task Adaptation with Large Language Models. CoRR abs/2312.07125 (2023) - 2022
- [c11]Jiaye Teng, Weiran Huang, Haowei He:
Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis. AISTATS 2022: 4198-4216 - [i15]Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang:
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. CoRR abs/2205.14814 (2022) - [i14]Manyi Zhang, Chun Yuan, Jun Yao, Weiran Huang:
Learning with Noisily-labeled Class-imbalanced Data. CoRR abs/2211.10955 (2022) - 2021
- [i13]Jiaye Teng, Weiran Huang:
Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis. CoRR abs/2103.03568 (2021) - [i12]Weiran Huang, Mingyang Yi, Xuyang Zhao:
Towards the Generalization of Contrastive Self-Supervised Learning. CoRR abs/2111.00743 (2021) - 2020
- [c10]Yimin Huang, Weiran Huang, Liang Li, Zhenguo Li:
Meta-Learning PAC-Bayes Priors in Model Averaging. AAAI 2020: 4198-4205 - [c9]Jiacheng Sun, Xiangyong Cao, Hanwen Liang, Weiran Huang, Zewei Chen, Zhenguo Li:
New Interpretations of Normalization Methods in Deep Learning. AAAI 2020: 5875-5882 - [c8]Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang:
Boosting Few-Shot Learning With Adaptive Margin Loss. CVPR 2020: 12573-12581 - [c7]Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang:
Locally Differentially Private (Contextual) Bandits Learning. NeurIPS 2020 - [i11]Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang:
Boosting Few-Shot Learning With Adaptive Margin Loss. CoRR abs/2005.13826 (2020) - [i10]Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang:
Locally Differentially Private (Contextual) Bandits Learning. CoRR abs/2006.00701 (2020) - [i9]Jiacheng Sun, Xiangyong Cao, Hanwen Liang, Weiran Huang, Zewei Chen, Zhenguo Li:
New Interpretations of Normalization Methods in Deep Learning. CoRR abs/2006.09104 (2020)
2010 – 2019
- 2019
- [c6]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: 5525-5532 - [c5]Aoxue Li, Tiange Luo, Tao Xiang, Weiran Huang, Liwei Wang:
Few-Shot Learning With Global Class Representations. ICCV 2019: 9714-9723 - [i8]Tiange Luo, Aoxue Li, Tao Xiang, Weiran Huang, Liwei Wang:
Few-Shot Learning with Global Class Representations. CoRR abs/1908.05257 (2019) - [i7]Hanwen Liang, Shifeng Zhang, Jiacheng Sun, Xingqiu He, Weiran Huang, Kechen Zhuang, Zhenguo Li:
DARTS+: Improved Differentiable Architecture Search with Early Stopping. CoRR abs/1909.06035 (2019) - [i6]Yimin Huang, Weiran Huang, Liang Li, Zhenguo Li:
Meta-Learning PAC-Bayes Priors in Model Averaging. CoRR abs/1912.11252 (2019) - 2018
- [c4]Weiran Huang, Jungseul Ok, Liang Li, Wei Chen:
Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications. IJCAI 2018: 2291-2297 - [c3]Lichao Sun, Weiran Huang, Philip S. Yu, Wei Chen:
Multi-Round Influence Maximization. KDD 2018: 2249-2258 - [c2]Xiaowei Chen, Weiran Huang, Wei Chen, John C. S. Lui:
Community Exploration: From Offline Optimization to Online Learning. NeurIPS 2018: 5479-5488 - [i5]Lichao Sun, Weiran Huang, Philip S. Yu, Wei Chen:
Multi-Round Influence Maximization (Extended Version). CoRR abs/1802.04189 (2018) - [i4]Weiran Huang, Jungseul Ok, Liang Li, Wei Chen:
Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications (Extended Version). CoRR abs/1805.01685 (2018) - [i3]Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu:
Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks. CoRR abs/1811.05121 (2018) - [i2]Xiaowei Chen, Weiran Huang, Wei Chen, John C. S. Lui:
Community Exploration: From Offline Optimization to Online Learning. CoRR abs/1811.05134 (2018) - 2017
- [c1]Weiran Huang, Liang Li, Wei Chen:
Partitioned Sampling of Public Opinions Based on Their Social Dynamics. AAAI 2017: 24-30 - 2015
- [i1]Weiran Huang, Liang Li, Wei Chen:
Partitioned Sampling of Public Opinions Based on Their Social Evolution. CoRR abs/1510.05217 (2015)
Coauthor Index
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last updated on 2024-10-23 21:27 CEST by the dblp team
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