Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Lalitha Sankar

Being Properly Improper


Jun 18, 2021
Richard Nock, Tyler Sypherd, Lalitha Sankar


  Access Paper or Ask Questions

Realizing GANs via a Tunable Loss Function


Jun 09, 2021
Gowtham R. Kurri, Tyler Sypherd, Lalitha Sankar

* 6 pages, 2 figures 

  Access Paper or Ask Questions

Three Variants of Differential Privacy: Lossless Conversion and Applications


Aug 14, 2020
Shahab Asoodeh, Jiachun Liao, Flavio P. Calmon, Oliver Kosut, Lalitha Sankar

* An extended version of our previous paper (arXiv:2001.05990) presented at ISIT'20 

  Access Paper or Ask Questions

On the alpha-loss Landscape in the Logistic Model


Jun 22, 2020
Tyler Sypherd, Mario Diaz, Lalitha Sankar, Gautam Dasarathy

* 5 pages, appeared in ISIT 2020 

  Access Paper or Ask Questions

A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via $f$-Divergences


Jan 16, 2020
Shahab Asoodeh, Jiachun Liao, Flavio P. Calmon, Oliver Kosut, Lalitha Sankar

* Submitted for Publication 

  Access Paper or Ask Questions

Theoretical Guarantees for Model Auditing with Finite Adversaries


Nov 08, 2019
Mario Diaz, Peter Kairouz, Jiachun Liao, Lalitha Sankar

* 18 pages, 1 figure 

  Access Paper or Ask Questions

Learning Generative Adversarial RePresentations (GAP) under Fairness and Censoring Constraints


Sep 27, 2019
Jiachun Liao, Chong Huang, Peter Kairouz, Lalitha Sankar

* 28 pages, 11 Figures. arXiv admin note: text overlap with arXiv:1807.05306 

  Access Paper or Ask Questions

A Tunable Loss Function for Classification


Jun 26, 2019
Tyler Sypherd, Mario Diaz, Harshit Laddha, Lalitha Sankar, Peter Kairouz, Gautam Dasarathy

* Corrected email address 

  Access Paper or Ask Questions

A Tunable Loss Function for Binary Classification


Mar 19, 2019
Tyler Sypherd, Mario Diaz, Lalitha Sankar, Peter Kairouz

* 9 pages, 1 figure, ISIT 2019 

  Access Paper or Ask Questions

Generative Adversarial Privacy


Jul 13, 2018
Chong Huang, Peter Kairouz, Xiao Chen, Lalitha Sankar, Ram Rajagopal

* A preliminary version of this work was presented at the Privacy in Machine Learning and Artificial Intelligence Workshop, ICML 2018. arXiv admin note: text overlap with arXiv:1710.09549 

  Access Paper or Ask Questions

Context-Aware Generative Adversarial Privacy


Dec 03, 2017
Chong Huang, Peter Kairouz, Xiao Chen, Lalitha Sankar, Ram Rajagopal

* Improved version of a paper accepted by Entropy Journal, Special Issue on Information Theory in Machine Learning and Data Science 

  Access Paper or Ask Questions