8 citations · 11 across the 2 of their papers we have counts for
3 papers
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning
Avrim Blum, Nika Haghtalab, Richard Lanas Phillips +1
In recent years, federated learning has been embraced as an approach for bringing about collaboration across large populations of learning agents. However, little is known about ho…
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund +20
Distribution shifts -- where the training distribution differs from the test distribution -- can substantially degrade the accuracy of machine learning (ML) systems deployed in the…
Disentangling Influence: Using Disentangled Representations to Audit Model Predictions
Charles T. Marx, Richard Lanas Phillips, Sorelle A. Friedler +2
Motivated by the need to audit complex and black box models, there has been extensive research on quantifying how data features influence model predictions. Feature influence can b…