[HTML][HTML] A deep learning framework to classify breast density with noisy labels regularization

H Lopez-Almazan, FJ Pérez-Benito, A Larroza… - Computer Methods and …, 2022 - Elsevier
Abstract Background and Objective Breast density assessed from digital mammograms is a
biomarker for higher risk of developing breast cancer. Experienced radiologists assess …

Robust product classification with instance-dependent noise

H Nguyen, D Khatwani - arXiv preprint arXiv:2209.06946, 2022 - arxiv.org
Noisy labels in large E-commerce product data (ie, product items are placed into incorrect
categories) are a critical issue for product categorization task because they are unavoidable …

AggMatch: Aggregating Pseudo Labels for Semi-Supervised Learning

J Kim, K Ryoo, G Lee, S Cho, J Seo, D Kim… - arXiv preprint arXiv …, 2022 - arxiv.org
Semi-supervised learning (SSL) has recently proven to be an effective paradigm for
leveraging a huge amount of unlabeled data while mitigating the reliance on large labeled …

An empirical investigation of learning from biased toxicity labels

N Nanda, J Uesato, S Gowal - arXiv preprint arXiv:2110.01577, 2021 - arxiv.org
Collecting annotations from human raters often results in a trade-off between the quantity of
labels one wishes to gather and the quality of these labels. As such, it is often only possible …