4 citations · 8 across the 8 of their papers we have counts for
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cs.LG2023
Probabilistic Invariant Learning with Randomized Linear Classifiers
Leonardo Cotta, Gal Yehuda, Assaf Schuster +1
Designing models that are both expressive and preserve known invariances of tasks is an increasingly hard problem. Existing solutions tradeoff invariance for computational or memor…
cs.LG2020
It's Not What Machines Can Learn, It's What We Cannot Teach
Gal Yehuda, Moshe Gabel, Assaf Schuster
Can deep neural networks learn to solve any task, and in particular problems of high complexity? This question attracts a lot of interest, with recent works tackling computationall…