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← Authors

Zhaowei Zhu

17 papers · 2021–2026 · 6 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+9 more ↓ πŸƒ Academic Marathon (5) 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (5)
πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (26) 🧭 Keyword Pioneer πŸ‘‘ Triple Crown 🀝 Dynamic Duo (16) πŸ† Grand Slam πŸ’Ž Century Club (16) πŸ—ƒοΈ Keyword Collector (56) πŸ”₯ Unstoppable (5)

Conferences

ICLR (6) ICML (5) AAAI (2) NIPS (2) CVPR (1) ECCV (1)

Top co-authors

Yang Liu (17) Hao Cheng (5) Jiaheng Wei (4) Jinlong Pang (3) Jialu Wang (3) Tongliang Liu (3) Chen Qian (3) Yuanshun Yao (2) Xing Sun (2) Gang Niu (2)

Keywords

label noise (4) transition matrix (2) label noise detection (1) model selection (1) policy learning (1) covariance estimation (1) feature representation (1) deep neural network (1) nearest neighbor (1) mutual information (1) weak supervision (1) second-order statistics (1) robust learning (1) generalization bound (1) reinforcement learning (1) bias mitigation (1) loss function (1) personalized model (1) influence function (1) active learning (1)

Papers

Robust Learning from Noisily Labeled Long-Tailed Data via Fairness Regularizer AAAI 2026 Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning ICML 2025 Improving Data Efficiency via Curating LLM-Driven Rating Systems ICLR 2025 Fairness without Harm: An Influence-Guided Active Sampling Approach NIPS 2024 FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning AAAI 2024 Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models ICLR 2024 Federated Learning with Local Openset Noisy Labels ECCV 2024 Mitigating Memorization of Noisy Labels via Regularization between Representations ICLR 2023 Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes ICML 2023 The Rich Get Richer: Disparate Impact of Semi-Supervised Learning ICLR 2022 Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations ICLR 2022 Detecting Corrupted Labels Without Training a Model to Predict ICML 2022 Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features ICML 2022 Policy Learning Using Weak Supervision NIPS 2021 A Second-Order Approach to Learning With Instance-Dependent Label Noise CVPR 2021 Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels ICML 2021 Learning with Instance-Dependent Label Noise: A Sample Sieve Approach ICLR 2021