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Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy
  Label Learning

Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning

5 March 2024
Heesun Bae
Seungjae Shin
Byeonghu Na
Il-Chul Moon
    NoLa
ArXivPDFHTML

Papers citing "Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning"

5 / 5 papers shown
Title
Label-Noise Robust Diffusion Models
Label-Noise Robust Diffusion Models
Byeonghu Na
Yeongmin Kim
Heesun Bae
Jung Hyun Lee
Seho Kwon
Wanmo Kang
Il-Chul Moon
NoLa
DiffM
58
8
0
27 Feb 2024
Do We Need to Penalize Variance of Losses for Learning with Label Noise?
Do We Need to Penalize Variance of Losses for Learning with Label Noise?
Yexiong Lin
Yu Yao
Yuxuan Du
Jun Yu
Bo Han
Biwei Huang
Tongliang Liu
NoLa
53
3
0
30 Jan 2022
Detecting Corrupted Labels Without Training a Model to Predict
Detecting Corrupted Labels Without Training a Model to Predict
Zhaowei Zhu
Zihao Dong
Yang Liu
NoLa
149
62
0
12 Oct 2021
Provably End-to-end Label-Noise Learning without Anchor Points
Provably End-to-end Label-Noise Learning without Anchor Points
Xuefeng Li
Tongliang Liu
Bo Han
Gang Niu
Masashi Sugiyama
NoLa
133
120
0
04 Feb 2021
Combating noisy labels by agreement: A joint training method with
  co-regularization
Combating noisy labels by agreement: A joint training method with co-regularization
Hongxin Wei
Lei Feng
Xiangyu Chen
Bo An
NoLa
319
498
0
05 Mar 2020
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