Clusterability as an Alternative to Anchor Points When Learning with
Noisy Labels

Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels

10 February 2021

Zhaowei Zhu

Yang Liu

Papers citing "Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels"

12 / 62 papers shown

Title
Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial Yang Liu Jialu Wang NoLa 19 18 0 13 Jul 2021
Adaptive Sample Selection for Robust Learning under Label Noise Deep Patel P. Sastry OOD NoLa 28 29 0 29 Jun 2021
To Smooth or Not? When Label Smoothing Meets Noisy Labels Jiaheng Wei Hangyu Liu Tongliang Liu Gang Niu Masashi Sugiyama Yang Liu NoLa 32 69 0 08 Jun 2021
Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network Shuo Yang Erkun Yang Bo Han Yang Liu Min Xu Gang Niu Tongliang Liu NoLa BDL 33 42 0 27 May 2021
Understanding Instance-Level Label Noise: Disparate Impacts and Treatments Yang Liu NoLa 8 35 0 10 Feb 2021
Provably End-to-end Label-Noise Learning without Anchor Points Xuefeng Li Tongliang Liu Bo Han Gang Niu Masashi Sugiyama NoLa 133 121 0 04 Feb 2021
An Empirical Study and Analysis on Open-Set Semi-Supervised Learning Huixiang Luo Hao Cheng Fanxu Meng Yuting Gao Ke Li Mengdan Zhang Xing Sun 25 8 0 19 Jan 2021
A Second-Order Approach to Learning with Instance-Dependent Label Noise Zhaowei Zhu Tongliang Liu Yang Liu NoLa 22 127 0 22 Dec 2020
Extended T: Learning with Mixed Closed-set and Open-set Noisy Labels Xiaobo Xia Tongliang Liu Bo Han Nannan Wang Jiankang Deng Jiatong Li Yinian Mao NoLa 24 11 0 02 Dec 2020
When Optimizing $f$ -divergence is Robust with Label Noise Jiaheng Wei Yang Liu 24 54 0 07 Nov 2020
Policy Learning Using Weak Supervision Jingkang Wang Hongyi Guo Zhaowei Zhu Yang Liu OffRL 27 14 0 05 Oct 2020
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 319 501 0 05 Mar 2020