536 citations · 4.4k across the 97 of their papers we have counts for
103 papers
A Simple Complexity Lower Bound for Solving
Ohad Shamir
In this note, we provide a short and direct proof that approximately solving to relative error , where has condition number and unrestricted dimension,…
Stronger Memory-Query Tradeoffs for Convex Optimization: The Limitations of Subquadratic Memory
Michael Menart, Aleksandar Nikolov, Ohad Shamir
We prove two lower bounds for the first order oracle complexity of minimizing a -dimensional -Lipschitz convex function over the unit ball with bits of memory. We first s…
Logarithmic Width Suffices for Robust Memorization
Amitsour Egosi, Gilad Yehudai, Ohad Shamir
The memorization capacity of neural networks with a given architecture has been thoroughly studied in many works. Specifically, it is well-known that memorizing samples can be…
Depth Separation in Norm-Bounded Infinite-Width Neural Networks
Suzanna Parkinson, Greg Ongie, Rebecca Willett +2
We study depth separation in infinite-width neural networks, where complexity is controlled by the overall squared -norm of the weights (sum of squares of all weights in th…
Generalization in Kernel Regression Under Realistic Assumptions
Daniel Barzilai, Ohad Shamir
It is by now well-established that modern over-parameterized models seem to elude the bias-variance tradeoff and generalize well despite overfitting noise. Many recent works attemp…
An Algorithm with Optimal Dimension-Dependence for Zero-Order Nonsmooth Nonconvex Stochastic Optimization
Guy Kornowski, Ohad Shamir
We study the complexity of producing -stationary points of Lipschitz objectives which are possibly neither smooth nor convex, using only noisy function evaluations. Recent w…