Zhaowei Zhu
17 papers · 2021–2026 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (38) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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(17)
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(5)
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Century Club Β· Bronze
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Keyword Collector
(86)
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Unstoppable Β· Bronze
Top co-authors
Research topics
Machine Learning
(16)
Learning Types Β· Machine Learning
(13)
Application Areas
(7)
Deep Learning
(5)
Core Methods
(5)
Artificial Intelligence
(4)
Core AI
(4)
Learning Types Β· Deep Learning
(4)
Natural Language Processing
(3)
Optimization & Theory Β· Deep Learning
(2)
Optimization & Theory Β· Machine Learning
(2)
Resources & Methods
(2)
Computer Vision
(1)
Mathematics & Optimization
(1)
Reinforcement Learning
(1)
Keywords
label noise
(7)
instance-dependent noise
(2)
deep neural network
(2)
noisy label
(2)
transition matrix
(2)
semi-supervised learning
(1)
reinforcement learning
(1)
active learning
(1)
knowledge distillation
(1)
weakly supervised learning
(1)
policy learning
(1)
covariance estimation
(1)
weak supervision
(1)
feature representation
(1)
label noise detection
(1)
mutual information
(1)
noisy label learning
(1)
nearest neighbor
(1)
second-order statistics
(1)
instruction tuning
(1)
Papers
Robust Learning from Noisily Labeled Long-Tailed Data via Fairness Regularizer
AAAI 2026
Improving Data Efficiency via Curating LLM-Driven Rating Systems
ICLR 2025
Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning
ICML 2025
Fairness without Harm: An Influence-Guided Active Sampling Approach
NeurIPS 2024
Federated Learning with Local Openset Noisy Labels
ECCV 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
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
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features
ICML 2022
Detecting Corrupted Labels Without Training a Model to Predict
ICML 2022
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations
ICLR 2022
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning
ICLR 2022
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
Policy Learning Using Weak Supervision
NeurIPS 2021