Learning From Noisy Labels Without Knowing Noise Rates

Learning from Noisy Labels without Knowing Noise Rates

Communications and Signal Processing Seminar Series

Boshen Zhang: Learning from Noisy Labels with Coarse-to-Fine Sample Credibility Modeling

Learning with Limited and Imperfect Data

DISC: Learning From Noisy Labels via Dynamic Instance-Specific Selection and Correction

Distilling Effective Supervision From Severe Label Noise

ComputerVisionFoundation Videos

What to do when annotators fail? Neural network training with noisy labels (Part I)

Adaptive Sample Selection for Robust Learning under Label Noise

ComputerVisionFoundation Videos

Day 1 Talk 4: Early-Learning Regularization Prevents Memorization of Noisy Labels (Carlos F.-Granda)

SLowDNN Workshop

Classification with unknown class conditional label noise on noncompact feature spaces

COLT

PNP: Robust Learning From Noisy Labels by Probabilistic Noise Prediction | CVPR 2022

Artificial Intelligence

[2021 CVPR] Joint Negative and Positive Learning for Noisy Labels

Video for CVPR 2023 paper "Fine-grained Classification with Noisy Labels"

PaperView: "Learning to Learn from Noisy Labeled Data"

WSDM-23 Workshops: To Aggregate or Not? Learning with Separate Noisy Labels

Association for Computing Machinery (ACM)

Labeling Noise in Deep Learning Models

Fair-OBNC: A Fairness Method For Label Noise

Feedzai | Fraud and Financial Crime

Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels (ICML 2020)

Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach

ComputerVisionFoundation Videos

WACV18: A Semi-Supervised Two-Stage Approach to Learning from Noisy Labels

ComputerVisionFoundation Videos

A Framework Using Contrastive Learning for Classification with Noisy Labels

What to do when annotators fail? Neural network training with noisy labels (Part II)