5 citations · 9 across the 3 of their papers we have counts for
6 papers
Test-time Assessment of a Model's Performance on Unseen Domains via Optimal Transport
Akshay Mehra, Yunbei Zhang, Jihun Hamm
Gauging the performance of ML models on data from unseen domains at test-time is essential yet a challenging problem due to the lack of labels in this setting. Moreover, the perfor…
Understanding the Robustness of Multi-Exit Models under Common Corruptions
Akshay Mehra, Skyler Seto, Navdeep Jaitly +1
Multi-Exit models (MEMs) use an early-exit strategy to improve the accuracy and efficiency of deep neural networks (DNNs) by allowing samples to exit the network before the last la…
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning
Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen +1
Unsupervised domain adaptation (UDA) enables cross-domain learning without target domain labels by transferring knowledge from a labeled source domain whose distribution differs fr…
Machine Learning with Electronic Health Records is vulnerable to Backdoor Trigger Attacks
Byunggill Joe, Akshay Mehra, Insik Shin +1
Electronic Health Records (EHRs) provide a wealth of information for machine learning algorithms to predict the patient outcome from the data including diagnostic information, vita…
How Robust are Randomized Smoothing based Defenses to Data Poisoning?
Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen +1
Predictions of certifiably robust classifiers remain constant in a neighborhood of a point, making them resilient to test-time attacks with a guarantee. In this work, we present a…
Fast Interactive Image Retrieval using large-scale unlabeled data
Akshay Mehra, Jihun Hamm, Mikhail Belkin
An interactive image retrieval system learns which images in the database belong to a user's query concept, by analyzing the example images and feedback provided by the user. The c…