Robust Learning Method

Robust learning methods aim to develop machine learning models that are resilient to various forms of data corruption, including noisy labels, adversarial attacks, and out-of-distribution samples. Current research focuses on developing algorithms that automatically identify and mitigate these corruptions, often employing techniques like variational inference, neighboring data analysis for real-time defense, and uncertainty estimation to improve model reliability. These advancements are crucial for enhancing the trustworthiness and reliability of machine learning models across diverse applications, particularly in safety-critical domains like healthcare and autonomous systems.

Papers

December 1, 2023

Adaptive Robust Learning using Latent Bernoulli Variables
Aleksandr Karakulev, Dave Zachariah, Prashant Singh
Variational Inference Robust Learning Robust Learning Method

September 29, 2023

Toward Robust Recommendation via Real-time Vicinal Defense
Yichang Xu, Chenwang Wu, Defu Lian
Recommender System Real Time Evasion Attack Robust Recommendation Robust Learning Method

February 15, 2023

Uncertainty-Estimation with Normalized Logits for Out-of-Distribution Detection
Mouxiao Huang, Yu Qiao
Distribution Detection Uncertainty Estimation Distribution Data Second Ranked Logits Uncertainty Score Robust Learning Method

January 14, 2023

Robust Remote Sensing Scene Classification with Multi-View Voting and Entropy Ranking
Jinyang Wang, Tao Wang, Min Gan, George Hadjichristofi
Deep Convolutional Neural Network Scene Classification Remote Sensing Scene Classification Robust Learning Method Entropy Score

September 5, 2022

A Robust Learning Methodology for Uncertainty-aware Scientific Machine Learning models
Erbet Costa Almeida, Carine de Menezes Rebello, Marcio Fontana, Leizer Schnitman, Idelfonso Bessa dos Reis Nogueira
Uncertainty Estimation Robust Learning Uncertainty Aware Model Uncertainty Decomposition SciML Model Robust Learning Method

June 9, 2022

Clustering with Queries under Semi-Random Noise
Alberto Del Pia, Mingchen Ma, Christos Tzamos
Query Information Parameter Free Linear Optimization Oracle Noise Distribution Robust Learning Method Random Model

January 31, 2022

Robust supervised learning with coordinate gradient descent
Stéphane Gaïffas, Ibrahim Merad
LeArning Abstract Robust Version Robust Learning Robust Estimation Coordinate Descent Robust Learning Method

December 5, 2021

Hard Sample Aware Noise Robust Learning for Histopathology Image Classification
Chuang Zhu, Wenkai Chen, Ting Peng, Ying Wang, Mulan Jin
Image Classification Noise Robust Learning Real World Noisy Datasets Robust Learning Method