Classification with Asymmetric Label Noise: Consistency and Maximal
Denoising

Classification with Asymmetric Label Noise: Consistency and Maximal Denoising

5 March 2013

Gilles Blanchard

Marek Flaska

Clayton Scott

Papers citing "Classification with Asymmetric Label Noise: Consistency and Maximal Denoising"

8 / 8 papers shown

Title
An Embedding is Worth a Thousand Noisy Labels Francesco Di Salvo Sebastian Doerrich Ines Rieger Christian Ledig NoLa 92 0 0 26 Aug 2024
Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels Curtis G. Northcutt Tailin Wu Isaac L. Chuang NoLa 36 159 0 04 May 2017
Recovering True Classifier Performance in Positive-Unlabeled Learning Shantanu Jain Martha White P. Radivojac 39 46 0 02 Feb 2017
Multiple Kernel Learning from Noisy Labels by Stochastic Programming Tianbao Yang M. Mahdavi Rong Jin Lijun Zhang Yang Zhou NoLa 41 27 0 18 Jun 2012
Noise Tolerance under Risk Minimization Naresh Manwani S. M. I. P. S. Sastry NoLa 122 273 0 24 Sep 2011
Multi-Instance Learning with Any Hypothesis Class Sivan Sabato Naftali Tishby 59 45 0 11 Jul 2011
Identifying Mislabeled Training Data C. Brodley M. Friedl 82 968 0 01 Jun 2011
Composite Binary Losses Mark D. Reid Robert C. Williamson 110 223 0 17 Dec 2009