SLIDE: Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning with Beidi Chen - #356
Beidi Chen is part of the team that developed a cheaper, algorithmic, CPU alternative to state-of-the-art GPU machines. They presented their findings at NeurIPS 2019 and have since gained a lot of att...
12 Mars 202031min
Advancements in Machine Learning with Sergey Levine - #355
Today we're joined by Sergey Levine, an Assistant Professor at UC Berkeley. We last heard from Sergey back in 2017, where we explored Deep Robotic Learning. Sergey and his lab’s recent efforts have be...
9 Mars 202043min
Secrets of a Kaggle Grandmaster with David Odaibo - #354
Imagine spending years learning ML from the ground up, from its theoretical foundations, but still feeling like you didn’t really know how to apply it. That’s where David Odaibo found himself in 2015,...
5 Mars 202041min
NLP for Mapping Physics Research with Matteo Chinazzi - #353
Predicting the future of science, particularly physics, is the task that Matteo Chinazzi, an associate research scientist at Northeastern University focused on in his paper Mapping the Physics Researc...
2 Mars 202035min
Metric Elicitation and Robust Distributed Learning with Sanmi Koyejo - #352
The unfortunate reality is that many of the most commonly used machine learning metrics don't account for the complex trade-offs that come with real-world decision making. This is one of the challenge...
27 Feb 202056min
High-Dimensional Robust Statistics with Ilias Diakonikolas - #351
Today we’re joined by Ilias Diakonikolas, faculty in the CS department at the University of Wisconsin-Madison, and author of the paper Distribution-Independent PAC Learning of Halfspaces with Massart ...
24 Feb 202036min
How AI Predicted the Coronavirus Outbreak with Kamran Khan - #350
Today we’re joined by Kamran Khan, founder & CEO of BlueDot, and professor of medicine and public health at the University of Toronto. BlueDot has been the recipient of a lot of attention for being th...
19 Feb 202051min
Turning Ideas into ML Powered Products with Emmanuel Ameisen - #349
Today we’re joined by Emmanuel Ameisen, machine learning engineer at Stripe, and author of the recently published book “Building Machine Learning Powered Applications; Going from Idea to Product.” In ...
17 Feb 202042min
