IEEE

Binary-Classifiers-Enabled Filters for Semi-Supervised Learning

Abstract: A typical semi-supervised learning-based scheme is based on training a single model for labeled data. For unlabeled data, it uses the pseudo-labeling method to obtain labels. However, the ...
IEEE

Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor Perturbation

Abstract: Deep learning (DL) classifiers are often unstable in that they may change significantly when retested on perturbed images or low quality images. This paper adds to the fundamental body of ...
Microsoft

Denoised smoothing: Provably defending pretrained classifiers against adversarial examples

Editor’s note: This post and its research are the result of the collaborative efforts of a team of researchers comprising former Microsoft Research Engineer Hadi Salman (opens in new tab), CMU PhD ...
GitHub

evaluateClassifiers_examples.rst

In the PyRBP, we integrate several machine learning classifiers from sklearn and implement several classical deep learning models for users to perform performance tests, for which we provide two ...