9 citations · 23 across the 12 of their papers we have counts for
4 papers · 1 filter
Extracting robust and accurate features via a robust information bottleneck
Ankit Pensia, Varun Jog, Po-Ling Loh
We propose a novel strategy for extracting features in supervised learning that can be used to construct a classifier which is more robust to small perturbations in the input space…
Robustifying deep networks for image segmentation
Zheng Liu, Jinnian Zhang, Varun Jog +2
Purpose: The purpose of this study is to investigate the robustness of a commonly-used convolutional neural network for image segmentation with respect to visually-subtle adversari…
Estimating location parameters in entangled single-sample distributions
Ankit Pensia, Varun Jog, Po-Ling Loh
We consider the problem of estimating the common mean of independently sampled data, where samples are drawn in a possibly non-identical manner from symmetric, unimodal distributio…
Does Data Augmentation Lead to Positive Margin?
Shashank Rajput, Zhili Feng, Zachary Charles +2
Data augmentation (DA) is commonly used during model training, as it significantly improves test error and model robustness. DA artificially expands the training set by applying ra…