281 citations · 1.2k across the 30 of their papers we have counts for
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cs.LG2019★ 10 cited
Robust Learning with the Hilbert-Schmidt Independence Criterion
Daniel Greenfeld, Uri Shalit
We investigate the use of a non-parametric independence measure, the Hilbert-Schmidt Independence Criterion (HSIC), as a loss-function for learning robust regression and classifica…
cs.LG2019
Off-Policy Evaluation in Partially Observable Environments
Guy Tennenholtz, Shie Mannor, Uri Shalit
This work studies the problem of batch off-policy evaluation for Reinforcement Learning in partially observable environments. Off-policy evaluation under partial observability is i…
cs.LG2019★ 92 cited
Explaining Classifiers with Causal Concept Effect (CaCE)
Yash Goyal, Amir Feder, Uri Shalit +1
How can we understand classification decisions made by deep neural networks? Many existing explainability methods rely solely on correlations and fail to account for confounding, w…