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Learning from Noisy Similar and Dissimilar Data

Learning from Noisy Similar and Dissimilar Data

Soham Dan
Han Bao
Masashi Sugiyama
    NoLa
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Papers citing "Learning from Noisy Similar and Dissimilar Data"

6 / 6 papers shown
Title
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
S. Du
Xiyu Zhai
Barnabás Póczós
Aarti Singh
MLTODL
245
1,276
0
04 Oct 2018
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang
Zhengyuan Zhou
Thomas Leung
Li Li
Li Fei-Fei
NoLa
140
1,459
0
14 Dec 2017
Learning from Binary Labels with Instance-Dependent Corruption
Learning from Binary Labels with Instance-Dependent Corruption
A. Menon
Brendan van Rooyen
Nagarajan Natarajan
NoLa
111
41
0
03 May 2016
Query Complexity of Derivative-Free Optimization
Query Complexity of Derivative-Free Optimization
Kevin Jamieson
Robert D. Nowak
Benjamin Recht
194
160
0
11 Sep 2012
Minimax testing of a composite null hypothesis defined via a quadratic functional in the model of regression
Minimax testing of a composite null hypothesis defined via a quadratic functional in the model of regression
L. Comminges
A. Dalalyan
138
58
0
09 Aug 2012
Active Ranking using Pairwise Comparisons
Active Ranking using Pairwise Comparisons
Kevin Jamieson
Robert D. Nowak
216
253
0
16 Sep 2011

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