Randall Balestriero

New York City, United States

Randall Balestriero is a postdoctorate researcher at FAIR in Prof. Yann LeCun's team. He mostly focuses on providing novel deep learning solutions which are inspired and supported by theoretical results. Hopefully, with the least amount of assumptions in the task, data, and model at hand. He has managed to successfully pursue this goal during his PhD using spline functions, and he is not working on further extending and generalizing those results e.g. for self-supervised learning.

Randall's Publications

SPEECH & AUDIO

RESEARCH

DeepHull: Fast Convex Hull Approximation in High Dimensions

Randall Balestriero, Richard G. Baraniuk, Zichao Wang

SPEECH & AUDIO

RESEARCH

No More Than 6Ft Apart: Robust K-Means via Radius Upper Bounds

Ahmed Imtiaz Humayun, Anastasios Kyrillidis, Randall Balestriero, Richard Baraniuk