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Min-Ling Zhang

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 15, 2026, 3:11 AM AMS

25

papers

254

total citations

papers (25)

Instance-Dependent Partial Label Learning

NEURIPS 2021arXiv

One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement

NEURIPS 2022arXiv

Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization

NEURIPS 2022arXiv

EAT: Towards Long-Tailed Out-of-Distribution Detection

Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning

NEURIPS 2023arXiv

Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning

Binary Classification with Confidence Difference

NEURIPS 2023arXiv

Realistic Evaluation of Deep Partial-Label Learning Algorithms

Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency

Implicit Relative Labeling-Importance Aware Multi-Label Metric Learning

Partial Label Causal Representation Learning for Instance-Dependent Supervision and Domain Generalization

Calibration Bottleneck: Over-compressed Representations are Less Calibratable

Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning

Learnware Specification via Label-Aware Neural Embedding

Generalization Analysis for Multi-Label Learning

Fast Multi-Instance Partial-Label Learning

Disentangled Partial Label Learning

Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence

On the Pitfall of Mixup for Uncertainty Calibration

Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition

Evolutionary Classifier Chain for Multi-Dimensional Classification

Long-Tailed Partial Label Learning by Head Classifier and Tail Classifier Cooperation

Efficient Model Stealing Defense with Noise Transition Matrix

Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization

Partial Multi-Label Learning with Probabilistic Graphical Disambiguation