Ming-Kun Xie
13 papers · 2020–2026 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+4 more ↓ Show less ↑
🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (23) 🌍 Conference Polyglot · Silver 🤝 Dynamic Duo (11)
🗃️
Keyword Collector
(64)
🔥
Unstoppable · Bronze
⚡
Prolific Year · Productive
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(10)
Learning Types · Machine Learning
(8)
Core Methods
(7)
Deep Learning
(2)
Reinforcement Learning
(2)
Application Areas
(2)
Methods
(2)
Optimization & Theory
(2)
Artificial Intelligence
(1)
Computer Vision
(1)
Knowledge & Reasoning
(1)
Core AI · Artificial Intelligence
(1)
Core AI · Computer Vision
(1)
Learning Paradigms
(1)
Learning Types · Deep Learning
(1)
Keywords
multi-label classification
(4)
label correlation
(2)
semi-supervised learning
(2)
label noise
(2)
knowledge distillation
(2)
multi-label learning
(2)
binary classification
(1)
policy optimization
(1)
contrastive learning
(1)
noisy label learning
(1)
vision transformer
(1)
policy learning
(1)
weak supervision
(1)
feature representation
(1)
label embedding
(1)
distribution shift
(1)
regularization
(1)
trace norm regularization
(1)
generalization bound
(1)
representation learning
(1)
Papers
FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning
CVPR 2026
Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning
CVPR 2025
Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL
ICML 2025
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training
ICML 2024
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels
AAAI 2024
Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-Supervised Multi-Label Learning
ECCV 2024
Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL
NeurIPS 2024
Unlocking the Power of Open Set: A New Perspective for Open-Set Noisy Label Learning
AAAI 2024
Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
NeurIPS 2023
Multi-Label Knowledge Distillation
ICCV 2023
Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels
NeurIPS 2022
Multi-Label Learning with Pairwise Relevance Ordering
NeurIPS 2021
Partial Multi-Label Learning with Noisy Label Identification
AAAI 2020