activity
20182022
most citedAdversarial Training Helps Transfer Learning via Better Representations

4 citations · 6 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

Development and Clinical Evaluation of an AI Support Tool for Improving Telemedicine Photo Quality

Kailas Vodrahalli, Justin Ko, Albert S. Chiou +7

Telemedicine utilization was accelerated during the COVID-19 pandemic, and skin conditions were a common use case. However, the quality of photographs sent by patients remains a ma…

cs.LG20214 cited

Adversarial Training Helps Transfer Learning via Better Representations

Zhun Deng, Linjun Zhang, Kailas Vodrahalli +2

Transfer learning aims to leverage models pre-trained on source data to efficiently adapt to target setting, where only limited data are available for model fine-tuning. Recent wor…

cs.LG2020

Better Knowledge Retention through Metric Learning

Ke Li, Shichong Peng, Kailas Vodrahalli +1

In continual learning, new categories may be introduced over time, and an ideal learning system should perform well on both the original categories and the new categories. While de…

cs.CV20201 cited

TrueImage: A Machine Learning Algorithm to Improve the Quality of Telehealth Photos

Kailas Vodrahalli, Roxana Daneshjou, Roberto A Novoa +3

Telehealth is an increasingly critical component of the health care ecosystem, especially due to the COVID-19 pandemic. Rapid adoption of telehealth has exposed limitations in the…

eess.SP2019

Blind interactive learning of modulation schemes: Multi-agent cooperation without co-design

Anant Sahai, Joshua Sanz, Vignesh Subramanian +2

We examine the problem of learning to cooperate in the context of wireless communication. In our setting, two agents must learn modulation schemes that enable them to communicate a…

cs.LG2019

Harmless interpolation of noisy data in regression

Vidya Muthukumar, Kailas Vodrahalli, Vignesh Subramanian +1

A continuing mystery in understanding the empirical success of deep neural networks is their ability to achieve zero training error and generalize well, even when the training data…