To Balance or Not to Balance: A Simple-yet-Effective Approach for
Learning with Long-Tailed Distributions

To Balance or Not to Balance: A Simple-yet-Effective Approach for Learning with Long-Tailed Distributions

10 December 2019

Lingqiao Liu

Peng Wang

Chunhua Shen

Papers citing "To Balance or Not to Balance: A Simple-yet-Effective Approach for Learning with Long-Tailed Distributions"

10 / 10 papers shown

Title
Cost-Sensitive Learning for Long-Tailed Temporal Action Segmentation Zhanzhong Pang Fadime Sener Shrinivas Ramasubramanian Angela Yao 56 1 0 24 Mar 2025
Dual Compensation Residual Networks for Class Imbalanced Learning Rui Hou Hong Chang Bingpeng Ma Shiguang Shan Xilin Chen 30 5 0 25 Aug 2023
The Curious Case of Benign Memorization Sotiris Anagnostidis Gregor Bachmann Lorenzo Noci Thomas Hofmann AAML 51 8 0 25 Oct 2022
ELM: Embedding and Logit Margins for Long-Tail Learning Wittawat Jitkrittum A. Menon A. S. Rawat Surinder Kumar 41 11 0 27 Apr 2022
AutoBalance: Optimized Loss Functions for Imbalanced Data Mingchen Li Xuechen Zhang Christos Thrampoulidis Jiasi Chen Samet Oymak 19 67 0 04 Jan 2022
Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis Mu Yang Shaojin Ding Tianlong Chen Tong Wang Zhangyang Wang CLL 30 5 0 09 Oct 2021
Deep Synoptic Monte Carlo Planning in Reconnaissance Blind Chess Gregory Clark 33 9 0 05 Oct 2021
Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification Peng Wang Kai Han Xiu-Shen Wei Lei Zhang Lei Wang SSL 35 233 0 26 Mar 2021
Long-tail learning via logit adjustment A. Menon Sadeep Jayasumana A. S. Rawat Himanshu Jain Andreas Veit Sanjiv Kumar 65 686 0 14 Jul 2020
Range Loss for Deep Face Recognition with Long-tail Xiao Zhang Zhiyuan Fang Yandong Wen Zhifeng Li Yu Qiao CVBM 243 447 0 28 Nov 2016