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High-Dimensional Robust Statistics with Ilias Diakonikolas

Ilias Diakonikolas is faculty in the Computer Science Department at the University of Wisconsin-Madison where his main research interests are in algorithms and machine learning. His work focuses on understanding the tradeoff between statistical efficiency, computational efficiency, and robustness for fundamental problems in statistics and machine learning, where robustness refers broadly to a model’s ability to deal with noisy data.

Ilias recently won the Outstanding Paper award at NeurIPS for his work, Distribution-Independent PAC Learning of Halfspaces with Massart Noise, which focuses on an area called high-dimensional robust learning and is essentially the first progress made around distribution-independent learning with noise since the 80s.

    *Nerd Alert!!* If you enjoy our more technical conversations, heads up that this interview won’t disappoint.

Learn with TWIML in 2020!

Hi Everyone, Happy New Year! TL;DR: I’m excited to announce a couple of new study group offerings in conjunction with our ever-expanding array of TWIML Community programs. One is focused on causality and the other on enterprise AI workflows. We’re collaborating with research scientist and instructor Robert Ness to bring his course sequence, Causal Modeling […]

We’re excited to share our third annual Black in AI series! When you’re done with this year’s series, make sure you check out the previous BAI series: Black in AI 2019 – Black in AI 2018 We’d love to hear your thoughts on this series, including anything we might have missed. Drop your thoughts, feedback […]

We’d love to hear your thoughts on this series, including anything we might have missed. Drop your thoughts, feedback or favorite papers via twitter @samcharrington, or via a comment below. TWIML Presents: KubeCon ’19 #343Scalable and Maintainable Workflows at Lyft with FlyteHaytham AbuelFutuh and Ketan Umare, Lyft TWIML Talk #344Managing Research Needs at the University […]

As is now customary around this time of year, we’ll be running back the clock with our second annual AI Rewind Series! Joined by a few friends of the show, we’ll be reviewing the papers, tools, use cases and other developments that made a splash in 2019 in key fields like Machine Learning, Deep Learning, […]

Thanks to our sponsor! Thanks to our friends at Shell for their support of the podcast and their sponsorship of the NeurIPS 2019 series. Shell has been an early adopter of a wide variety of AI technologies to support use cases across retail, trading, new energies, refineries, exploration, and many more, and is doing some […]