1.9k citations · 6.5k across the 132 of their papers we have counts for
13 papers · 1 filter
Simple Surveys: Response Retrieval Inspired by Recommendation Systems
Nandana Sengupta, Nati Srebro, James Evans
In the last decade, the use of simple rating and comparison surveys has proliferated on social and digital media platforms to fuel recommendations. These simple surveys and their e…
From Fair Decision Making to Social Equality
Hussein Mozannar, Mesrob I. Ohannessian, Nathan Srebro
The study of fairness in intelligent decision systems has mostly ignored long-term influence on the underlying population. Yet fairness considerations (e.g. affirmative action) hav…
On preserving non-discrimination when combining expert advice
Avrim Blum, Suriya Gunasekar, Thodoris Lykouris +1
We study the interplay between sequential decision making and avoiding discrimination against protected groups, when examples arrive online and do not follow distributional assumpt…
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
Andrew Cotter, Maya Gupta, Heinrich Jiang +5
Classifiers can be trained with data-dependent constraints to satisfy fairness goals, reduce churn, achieve a targeted false positive rate, or other policy goals. We study the gene…
A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates
Yossi Arjevani, Ohad Shamir, Nathan Srebro
We provide tight finite-time convergence bounds for gradient descent and stochastic gradient descent on quadratic functions, when the gradients are delayed and reflect iterates fro…
Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate
Mor Shpigel Nacson, Nathan Srebro, Daniel Soudry
Stochastic Gradient Descent (SGD) is a central tool in machine learning. We prove that SGD converges to zero loss, even with a fixed (non-vanishing) learning rate - in the special…