Cover Image

Embracing Biased Transition Matrices for Complementary-Label Learning with Many Classes

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mai, Tan-Ha, Chiang, Chao-Kai, Shih, Han-Hwa, Niu, Gang, Sugiyama, Masashi, Lin, Hsuan-Tien
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Intra-Cluster Mixup: An Effective Data Augmentation Technique for Complementary-Label Learning
by: Mai, Tan-Ha, et al.
Published: (2025)

CLImage: Human-Annotated Datasets for Complementary-Label Learning
by: Wang, Hsiu-Hsuan, et al.
Published: (2023)

libcll: an Extendable Python Toolkit for Complementary-Label Learning
by: Ye, Nai-Xuan, et al.
Published: (2024)

Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical
by: Wang, Wei, et al.
Published: (2023)

Decoupling the Class Label and the Target Concept in Machine Unlearning
by: Zhu, Jianing, et al.
Published: (2024)

LLM Routing with Dueling Feedback
by: Chiang, Chao-Kai, et al.
Published: (2025)

Label Distribution Learning with Biased Annotations by Learning Multi-Label Representation
by: Kou, Zhiqiang, et al.
Published: (2025)

Domain Adaptation and Entanglement: an Optimal Transport Perspective
by: Koç, Okan, et al.
Published: (2025)

Rethinking Consistent Multi-Label Classification Under Inexact Supervision
by: Wang, Wei, et al.
Published: (2025)

Realistic Evaluation of Deep Partial-Label Learning Algorithms
by: Wang, Wei, et al.
Published: (2025)

Learning from Hard Labels with Additional Supervision on Non-Hard-Labeled Classes
by: Sugiyama, Kosuke, et al.
Published: (2025)

Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-Supervised Multi-Label Learning
by: Xiao, Jia-Hao, et al.
Published: (2024)

Towards Scalable Oversight with Collaborative Multi-Agent Debate in Error Detection
by: Chen, Yongqiang, et al.
Published: (2025)

Learning from Complementary Features
by: Sugiyama, Kosuke, et al.
Published: (2024)

Robust Multi-View Learning via Representation Fusion of Sample-Level Attention and Alignment of Simulated Perturbation
by: Xu, Jie, et al.
Published: (2025)

Multi-Label Knowledge Distillation
by: Yang, Penghui, et al.
Published: (2023)

Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought
by: Zhang, Zhen-Yu, et al.
Published: (2024)

Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training
by: Xie, Ming-Kun, et al.
Published: (2024)

Class-Imbalanced Complementary-Label Learning via Weighted Loss
by: Wei, Meng, et al.
Published: (2022)

BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning
by: Zhang, Jingfeng, et al.
Published: (2023)

What Is Preference Optimization Doing, and Why?
by: Wang, Yue, et al.
Published: (2025)

BrokenBind: Universal Modality Exploration beyond Dataset Boundaries
by: Huang, Zhuo, et al.
Published: (2026)

Accessible, Realistic, and Fair Evaluation of Positive-Unlabeled Learning Algorithms
by: Wang, Wei, et al.
Published: (2025)

Balancing Similarity and Complementarity for Federated Learning
by: Yan, Kunda, et al.
Published: (2024)

Reinforcement Learning with Verifiable yet Noisy Rewards under Imperfect Verifiers
by: Cai, Xin-Qiang, et al.
Published: (2025)

In-context Demonstration Matters: On Prompt Optimization for Pseudo-Supervision Refinement
by: Zhang, Zhen-Yu, et al.
Published: (2024)

Decomposing the Basic Abilities of Large Language Models: Mitigating Cross-Task Interference in Multi-Task Instruct-Tuning
by: Wang, Bing, et al.
Published: (2026)

Accurate Forgetting for Heterogeneous Federated Continual Learning
by: Wuerkaixi, Abudukelimu, et al.
Published: (2025)

Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance
by: Huang, Paul Kuo-Ming, et al.
Published: (2023)

Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations
by: Chen, Hao, et al.
Published: (2023)

Constrained Pricing in Choice-based Revenue Management
by: Shao, Qian, et al.
Published: (2025)

Reinforcement Learning with Options and State Representation
by: Ghriss, Ayoub, et al.
Published: (2024)

VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates
by: Braun, Guillaume, et al.
Published: (2024)

A Fast Algorithm for the Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit
by: Nakamura, Shintaro, et al.
Published: (2023)

Riemannian Langevin Dynamics: Strong Convergence of Geometric Euler-Maruyama Scheme
by: Zhan, Zhiyuan, et al.
Published: (2026)

Enriching Disentanglement: From Logical Definitions to Quantitative Metrics
by: Zhang, Yivan, et al.
Published: (2023)

Parallel Simulation for Log-concave Sampling and Score-based Diffusion Models
by: Zhou, Huanjian, et al.
Published: (2024)

A Category-theoretical Meta-analysis of Definitions of Disentanglement
by: Zhang, Yivan, et al.
Published: (2023)

Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
by: Hsu, Kyle, et al.
Published: (2024)

Offline Reinforcement Learning from Datasets with Structured Non-Stationarity
by: Ackermann, Johannes, et al.
Published: (2024)