BLIA: Detect model memorization in binary classification model through passive Label Inference attack
Authors: Mohammad Wahiduzzaman Khan, Sheng Chen, Ilya Mironov, Leizhen Zhang, Rabib Noor | Published: 2025-03-17
Data Curation
A Decade’s Battle on Dataset Bias: Are We There Yet?
Authors: Zhuang Liu, Kaiming He | Published: 2024-03-13 | Updated: 2025-03-03
Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
Authors: Curtis G. Northcutt, Anish Athalye, Jonas Mueller | Published: 2021-03-26 | Updated: 2021-11-07
Identifying Statistical Bias in Dataset Replication
Authors: Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry | Published: 2020-05-19 | Updated: 2020-09-02
Confident Learning: Estimating Uncertainty in Dataset Labels
Authors: Curtis G. Northcutt, Lu Jiang, Isaac L. Chuang | Published: 2019-10-31 | Updated: 2022-08-22
ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation
Authors: Ethan M. Rudd, Felipe N. Ducau, Cody Wild, Konstantin Berlin, Richard Harang | Published: 2019-03-13
Natural and Adversarial Error Detection using Invariance to Image Transformations
Authors: Yuval Bahat, Michal Irani, Gregory Shakhnarovich | Published: 2019-02-01
Learning with Bad Training Data via Iterative Trimmed Loss Minimization
Authors: Yanyao Shen, Sujay Sanghavi | Published: 2018-10-28 | Updated: 2019-02-18
Sparse DNNs with Improved Adversarial Robustness
Authors: Yiwen Guo, Chao Zhang, Changshui Zhang, Yurong Chen | Published: 2018-10-23 | Updated: 2019-11-06
Curriculum Adversarial Training
Authors: Qi-Zhi Cai, Min Du, Chang Liu, Dawn Song | Published: 2018-05-13