most citedSmoothed Analysis of Sequential Probability Assignment

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

cond-mat.soft2024

Jamming memory into acoustically trained dense suspensions under shear

Edward Y. X. Ong, Anna R. Barth, Navneet Singh +5

Systems driven far from equilibrium often retain structural memories of their processing history. This memory has, in some cases, been shown to dramatically alter the material resp…

stat.ML2024

On the Performance of Empirical Risk Minimization with Smoothed Data

Adam Block, Alexander Rakhlin, Abhishek Shetty

In order to circumvent statistical and computational hardness results in sequential decision-making, recent work has considered smoothed online learning, where the distribution of…

stat.ML2024

Oracle-Efficient Differentially Private Learning with Public Data

Adam Block, Mark Bun, Rathin Desai +2

Due to statistical lower bounds on the learnability of many function classes under privacy constraints, there has been recent interest in leveraging public data to improve the perf…

cond-mat.soft2023

The manifold rheology of fluidized granular media

Olfa D'Angelo, Abhishek Shetty, Matthias Sperl +1

Fluidized granular media have a rich rheology: measuring shear stress as a function of shear rate , they exhibit Newtonian behavior for low densities and sh…

cs.LG2023

Optimal PAC Bounds Without Uniform Convergence

Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty +1

In statistical learning theory, determining the sample complexity of realizable binary classification for VC classes was a long-standing open problem. The results of Simon and Hann…

cs.LG20231 cited

Smoothed Analysis of Sequential Probability Assignment

Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty

We initiate the study of smoothed analysis for the sequential probability assignment problem with contexts. We study information-theoretically optimal minmax rates as well as a fra…