A Simple yet Effective Baseline for Robust Deep Learning with Noisy
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A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels

20 September 2019

Jun Zhu

Tomas Pfister

Papers citing "A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels"

4 / 4 papers shown

Title
A Learning Paradigm for Interpretable Gradients Felipe Figueroa Hanwei Zhang R. Sicre Yannis Avrithis Stéphane Ayache FAtt 23 0 0 23 Apr 2024
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 267 1,275 0 06 Mar 2017
Learning from Binary Labels with Instance-Dependent Corruption A. Menon Brendan van Rooyen Nagarajan Natarajan NoLa 31 41 0 03 May 2016
Bayesian Inference with Posterior Regularization and applications to Infinite Latent SVMs Jun Zhu Ning Chen Eric P. Xing BDL 67 157 0 05 Oct 2012