Coresets for Robust Training of Neural Networks against Noisy Labels

Coresets for Robust Training of Neural Networks against Noisy Labels

15 November 2020

Baharan Mirzasoleiman

Papers citing "Coresets for Robust Training of Neural Networks against Noisy Labels"

11 / 11 papers shown

Title
Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled yet Hard-to-Learn Samples in Noisy Data Weiran Pan Wei Wei Feida Zhu Yong Deng NoLa 167 0 0 24 Apr 2025
Sample Selection via Contrastive Fragmentation for Noisy Label Regression C. Kim Sangwoo Moon Jihwan Moon Dongyeon Woo Gunhee Kim NoLa 57 0 0 25 Feb 2025
Soft Random Sampling: A Theoretical and Empirical Analysis Xiaodong Cui Ashish R. Mittal Songtao Lu Wei Zhang G. Saon Brian Kingsbury 48 1 0 21 Nov 2023
MILD: Modeling the Instance Learning Dynamics for Learning with Noisy Labels Chuanyan Hu Shipeng Yan Zhitong Gao Xuming He NoLa 24 4 0 20 Jun 2023
GDOD: Effective Gradient Descent using Orthogonal Decomposition for Multi-Task Learning Xin Dong Ruize Wu Chao Xiong Hai Li Lei Cheng Yong He Shiyou Qian Jian Cao Linjian Mo 6 4 0 31 Jan 2023
Denoising after Entropy-based Debiasing A Robust Training Method for Dataset Bias with Noisy Labels Sumyeong Ahn Se-Young Yun NoLa 29 2 0 01 Dec 2022
Efficient NTK using Dimensionality Reduction Nir Ailon Supratim Shit 31 0 0 10 Oct 2022
SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels Yangdi Lu Wenbo He NoLa 37 39 0 02 May 2022
Obstacle Aware Sampling for Path Planning M. Tukan Alaa Maalouf Dan Feldman Roi Poranne 31 8 0 08 Mar 2022
Minimax Optimization: The Case of Convex-Submodular Arman Adibi Aryan Mokhtari Hamed Hassani 18 7 0 01 Nov 2021
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training Krishnateja Killamsetty D. Sivasubramanian Ganesh Ramakrishnan A. De Rishabh K. Iyer OOD 94 188 0 27 Feb 2021