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REPORTS > AUTHORS > ILIAS DIAKONIKOLAS:
All reports by Author Ilias Diakonikolas:

TR22-178 | 8th December 2022
Ilias Diakonikolas, Christos Tzamos, Daniel Kane

A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning

The Forster transform is a method of regularizing a dataset
by placing it in {\em radial isotropic position}
while maintaining some of its essential properties.
Forster transforms have played a key role in a diverse range of settings
spanning computer science and functional analysis. Prior work had given
{\em ... more >>>


TR20-140 | 14th September 2020
Ilias Diakonikolas, Themis Gouleakis, Daniel Kane, John Peebles, Eric Price

Optimal Testing of Discrete Distributions with High Probability

We study the problem of testing discrete distributions with a focus on the high probability regime.
Specifically, given samples from one or more discrete distributions, a property $\mathcal{P}$, and
parameters $0< \epsilon, \delta <1$, we want to distinguish {\em with probability at least $1-\delta$}
whether these distributions satisfy $\mathcal{P}$ ... more >>>




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