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Exponentiated Gradient Reweighting for Robust Training Under Label Noise
  and Beyond

Exponentiated Gradient Reweighting for Robust Training Under Label Noise and Beyond

3 April 2021
Negin Majidi
Ehsan Amid
Hossein Talebi
Manfred K. Warmuth
    NoLa
ArXiv (abs)PDFHTML

Papers citing "Exponentiated Gradient Reweighting for Robust Training Under Label Noise and Beyond"

15 / 15 papers shown
Title
Mirror Descent Using the Tempesta Generalized Multi-parametric Logarithms
Mirror Descent Using the Tempesta Generalized Multi-parametric Logarithms
Andrzej Cichocki
19
0
0
08 Jun 2025
HAM: A Hyperbolic Step to Regulate Implicit Bias
HAM: A Hyperbolic Step to Regulate Implicit Bias
Tom Jacobs
Advait Gadhikar
Celia Rubio-Madrigal
R. Burkholz
74
0
0
03 Jun 2025
Energy-based Preference Optimization for Test-time Adaptation
Energy-based Preference Optimization for Test-time Adaptation
Yewon Han
Seoyun Yang
Taesup Kim
TTA
278
0
0
26 May 2025
Mirror Descent and Novel Exponentiated Gradient Algorithms Using Trace-Form Entropies and Deformed Logarithms
Mirror Descent and Novel Exponentiated Gradient Algorithms Using Trace-Form Entropies and Deformed Logarithms
Andrzej Cichocki
Toshihisa Tanaka
S. Cruces
102
1
0
11 Mar 2025
Generalized Exponentiated Gradient Algorithms Using the Euler Two-Parameter Logarithm
Generalized Exponentiated Gradient Algorithms Using the Euler Two-Parameter Logarithm
Andrzej Cichocki
74
2
0
21 Feb 2025
Adaptive Deviation Learning for Visual Anomaly Detection with Data
  Contamination
Adaptive Deviation Learning for Visual Anomaly Detection with Data Contamination
Anindya Sundar Das
Guansong Pang
M. Bhuyan
61
1
0
14 Nov 2024
FPR Estimation for Fraud Detection in the Presence of Class-Conditional
  Label Noise
FPR Estimation for Fraud Detection in the Presence of Class-Conditional Label Noise
Justin Tittelfitz
64
0
0
04 Aug 2023
Stochastic Re-weighted Gradient Descent via Distributionally Robust
  Optimization
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
Ramnath Kumar
Kushal Majmundar
Dheeraj M. Nagaraj
A. Suggala
ODL
64
6
0
15 Jun 2023
SLaM: Student-Label Mixing for Distillation with Unlabeled Examples
SLaM: Student-Label Mixing for Distillation with Unlabeled Examples
Vasilis Kontonis
Fotis Iliopoulos
Khoa Trinh
Cenk Baykal
Gaurav Menghani
Erik Vee
78
8
0
08 Feb 2023
Weighted Distillation with Unlabeled Examples
Weighted Distillation with Unlabeled Examples
Fotis Iliopoulos
Vasilis Kontonis
Cenk Baykal
Gaurav Menghani
Khoa Trinh
Erik Vee
61
12
0
13 Oct 2022
To Aggregate or Not? Learning with Separate Noisy Labels
To Aggregate or Not? Learning with Separate Noisy Labels
Jiaheng Wei
Zhaowei Zhu
Tianyi Luo
Ehsan Amid
Abhishek Kumar
Yang Liu
NoLa
77
40
0
14 Jun 2022
A Robust Optimization Method for Label Noisy Datasets Based on Adaptive
  Threshold: Adaptive-k
A Robust Optimization Method for Label Noisy Datasets Based on Adaptive Threshold: Adaptive-k
Enes Dedeoglu
Himmet Toprak Kesgin
M. Amasyalı
NoLa
44
2
0
26 Mar 2022
Constrained Instance and Class Reweighting for Robust Learning under
  Label Noise
Constrained Instance and Class Reweighting for Robust Learning under Label Noise
Abhishek Kumar
Ehsan Amid
NoLa
61
20
0
09 Nov 2021
To Smooth or Not? When Label Smoothing Meets Noisy Labels
To Smooth or Not? When Label Smoothing Meets Noisy Labels
Jiaheng Wei
Hangyu Liu
Tongliang Liu
Gang Niu
Masashi Sugiyama
Yang Liu
NoLa
135
72
0
08 Jun 2021
Attentional-Biased Stochastic Gradient Descent
Attentional-Biased Stochastic Gradient Descent
Q. Qi
Yi Tian Xu
Rong Jin
W. Yin
Tianbao Yang
ODL
84
12
0
13 Dec 2020
1