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Adversarial Label Learning

Adversarial Label Learning

22 May 2018
Chidubem Arachie
Bert Huang
ArXivPDFHTML

Papers citing "Adversarial Label Learning"

9 / 9 papers shown
Title
An Adaptive Method for Weak Supervision with Drifting Data
An Adaptive Method for Weak Supervision with Drifting Data
Alessio Mazzetto
Reza Esfandiarpoor
E. Upfal
Stephen H. Bach
Stephen H. Bach
65
1
0
02 Jun 2023
Robust Knowledge Distillation from RNN-T Models With Noisy Training
  Labels Using Full-Sum Loss
Robust Knowledge Distillation from RNN-T Models With Noisy Training Labels Using Full-Sum Loss
Mohammad Zeineldeen
Kartik Audhkhasi
M. Baskar
Bhuvana Ramabhadran
24
2
0
10 Mar 2023
Regularized Data Programming with Automated Bayesian Prior Selection
Regularized Data Programming with Automated Bayesian Prior Selection
Jacqueline R. M. A. Maasch
Hao Zhang
Qian Yang
Fei Wang
Volodymyr Kuleshov
34
0
0
17 Oct 2022
Training Subset Selection for Weak Supervision
Training Subset Selection for Weak Supervision
Hunter Lang
Aravindan Vijayaraghavan
David Sontag
NoLa
8
21
0
06 Jun 2022
A Survey on Programmatic Weak Supervision
A Survey on Programmatic Weak Supervision
Jieyu Zhang
Cheng-Yu Hsieh
Yue Yu
Chao Zhang
Alexander Ratner
24
91
0
11 Feb 2022
Data Consistency for Weakly Supervised Learning
Data Consistency for Weakly Supervised Learning
Chidubem Arachie
Bert Huang
NoLa
22
2
0
08 Feb 2022
Constrained Labeling for Weakly Supervised Learning
Constrained Labeling for Weakly Supervised Learning
Chidubem Arachie
Bert Huang
15
18
0
15 Sep 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible
Confidence Scores Make Instance-dependent Label-noise Learning Possible
Antonin Berthon
Bo Han
Gang Niu
Tongliang Liu
Masashi Sugiyama
NoLa
21
104
0
11 Jan 2020
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave
  Saddle Point Problems without Strong Convexity
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity
S. Du
Wei Hu
53
120
0
05 Feb 2018
1