L. Sankar

activity

20072026

most citedUtility-Privacy Tradeoff in Databases: An Information-theoretic Approach

388 citations · 1.5k across the 94 of their papers we have counts for

collaborators

Showing 2019 · cs.LGShow all

3 papers · 2 filters

cs.LG2019★ 1 cited

Generating Fair Universal Representations using Adversarial Models

Peter Kairouz, Jiachun Liao, Chong Huang +3

We present a data-driven framework for learning fair universal representations (FUR) that guarantee statistical fairness for any learning task that may not be known a priori. Our f…

cs.LG2019★ 2 cited

A Tunable Loss Function for Robust Classification: Calibration, Landscape, and Generalization

Tyler Sypherd, Mario Diaz, John Kevin Cava +3

We introduce a tunable loss function called $α$ -loss, parameterized by $α \in (0, \infty]$ , which interpolates between the exponential loss ( $α = 1/2$ ), the log-loss ( $α = 1$ ), and the…

cs.LG2019

A Tunable Loss Function for Binary Classification

Tyler Sypherd, Mario Diaz, Lalitha Sankar +1

We present $α$ -loss, $α \in [1, \infty]$ , a tunable loss function for binary classification that bridges log-loss ( $α = 1$ ) and $0$ - $1$ loss ( $α = \infty$ ). We prove that $α$ -loss has a…