419 citations · 3.1k across the 71 of their papers we have counts for
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SelfieBoost: A Boosting Algorithm for Deep Learning
Shai Shalev-Shwartz
We describe and analyze a new boosting algorithm for deep learning called SelfieBoost. Unlike other boosting algorithms, like AdaBoost, which construct ensembles of classifiers, Se…
On the Computational Efficiency of Training Neural Networks
Roi Livni, Shai Shalev-Shwartz, Ohad Shamir
It is well-known that neural networks are computationally hard to train. On the other hand, in practice, modern day neural networks are trained efficiently using SGD and a variety…
Optimal Learners for Multiclass Problems
Amit Daniely, Shai Shalev-Shwartz
The fundamental theorem of statistical learning states that for binary classification problems, any Empirical Risk Minimization (ERM) learning rule has close to optimal sample comp…
Complexity theoretic limitations on learning DNF's
Amit Daniely, Shai Shalev-Shwatz
Using the recently developed framework of [Daniely et al, 2014], we show that under a natural assumption on the complexity of refuting random K-SAT formulas, learning DNF formulas…
Subspace Learning with Partial Information
Alon Gonen, Dan Rosenbaum, Yonina Eldar +1
The goal of subspace learning is to find a -dimensional subspace of , such that the expected squared distance between instance vectors and the subspace is as small…