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Optimally Combining Classifiers Using Unlabeled Data
v1v2v3 (latest)

Optimally Combining Classifiers Using Unlabeled Data

5 March 2015
Akshay Balsubramani
Y. Freund
ArXiv (abs)PDFHTML

Papers citing "Optimally Combining Classifiers Using Unlabeled Data"

16 / 16 papers shown
Title
Entropy, concentration, and learning: a statistical mechanics primer
Entropy, concentration, and learning: a statistical mechanics primer
Akshay Balsubramani
AI4CE
149
1
0
27 Sep 2024
Convergence Behavior of an Adversarial Weak Supervision Method
Convergence Behavior of an Adversarial Weak Supervision Method
Steven An
Sanjoy Dasgupta
115
1
0
25 May 2024
An Adaptive Method for Weak Supervision with Drifting Data
An Adaptive Method for Weak Supervision with Drifting DataInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Alessio Mazzetto
Reza Esfandiarpoor
E. Upfal
Stephen H. Bach
Stephen H. Bach
203
1
0
02 Jun 2023
Losses over Labels: Weakly Supervised Learning via Direct Loss
  Construction
Losses over Labels: Weakly Supervised Learning via Direct Loss ConstructionAAAI Conference on Artificial Intelligence (AAAI), 2022
Dylan Sam
J. Zico Kolter
NoLaOffRL
216
13
0
13 Dec 2022
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with
  Attributes
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with AttributesNeural Information Processing Systems (NeurIPS), 2022
Alessio Mazzetto
Cristina Menghini
A. Yuan
E. Upfal
Stephen H. Bach
VLM
113
2
0
25 May 2022
Data Consistency for Weakly Supervised Learning
Data Consistency for Weakly Supervised Learning
Chidubem Arachie
Bert Huang
NoLa
110
2
0
08 Feb 2022
Minimax risk classifiers with 0-1 loss
Minimax risk classifiers with 0-1 lossJournal of machine learning research (JMLR), 2022
Santiago Mazuelas
Mauricio Romero
Peter Grünwald
253
6
0
17 Jan 2022
Dash: Semi-Supervised Learning with Dynamic Thresholding
Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Tian Xu
Lei Shang
Jinxing Ye
Qi Qian
Yu-Feng Li
Baigui Sun
Hao Li
Rong Jin
184
258
0
01 Sep 2021
Learning from Multiple Noisy Partial Labelers
Learning from Multiple Noisy Partial LabelersInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Peilin Yu
Tiffany Ding
Stephen H. Bach
NoLa
148
24
0
08 Jun 2021
Stochastic Generalized Adversarial Label Learning
Stochastic Generalized Adversarial Label Learning
Chidubem Arachie
Bert Huang
NoLa
68
0
0
03 Jun 2019
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness
Lan-Zhe Guo
Yu-Feng Li
Ming Li
Jinfeng Yi
Bowen Zhou
Zhi Zhou
73
2
0
22 Apr 2019
Optimal Binary Autoencoding with Pairwise Correlations
Optimal Binary Autoencoding with Pairwise Correlations
Akshay Balsubramani
SSL
84
1
0
07 Nov 2016
Muffled Semi-Supervised Learning
Muffled Semi-Supervised Learning
Akshay Balsubramani
Y. Freund
41
0
0
28 May 2016
Learning to Abstain from Binary Prediction
Learning to Abstain from Binary Prediction
Akshay Balsubramani
88
8
0
25 Feb 2016
Optimal Binary Classifier Aggregation for General Losses
Optimal Binary Classifier Aggregation for General Losses
Akshay Balsubramani
Y. Freund
208
12
0
01 Oct 2015
Scalable Semi-Supervised Aggregation of Classifiers
Scalable Semi-Supervised Aggregation of Classifiers
Akshay Balsubramani
Y. Freund
102
7
0
18 Jun 2015
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