From the 2 of 23 linked papers with an AI index.
12 papers · 1 filter
High-Dimensional Gaussian Mean Estimation under Realizable Contamination
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas
The paper investigates estimating the mean of a high‑dimensional Gaussian when each sample may be missing with a bounded, data‑dependent probability (realizable ε‑contamination), p…
Robust Regression of General ReLUs with Queries
Ilias Diakonikolas, Daniel M. Kane, Mingchen Ma
We study the task of agnostically learning general (as opposed to homogeneous) ReLUs under the Gaussian distribution with respect to the squared loss. In the passive learning setti…
Sample Complexity Bounds for Robust Mean Estimation with Mean-Shift Contamination
Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane +1
We study the basic task of mean estimation in the presence of mean-shift contamination. In the mean-shift contamination model, an adversary is allowed to replace a small constant f…
Statistical Query Lower Bounds for Smoothed Agnostic Learning
Ilias Diakonikolas, Daniel M. Kane
We study the complexity of smoothed agnostic learning, recently introduced by~\cite{CKKMS24}, in which the learner competes with the best classifier in a target class under slight…
Replicable Distribution Testing
Ilias Diakonikolas, Jingyi Gao, Daniel Kane +2
We initiate a systematic investigation of distribution testing in the framework of algorithmic replicability. Specifically, given independent samples from a collection of probabili…
Algorithms and SQ Lower Bounds for Robustly Learning Real-valued Multi-index Models
Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane +1
We study the complexity of learning real-valued Multi-Index Models (MIMs) under the Gaussian distribution. A -MIM is a function that depends only…