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Underrated ML


Listen along as we try and dissect various Machine Learning papers that just haven't got the love and attention they deserve.Twitter: Page:

Popular episodes

Ari Morcos - The importance of of certain layers in DNNs

Nov 2 • 57:15

This week we are joined by Ari Morcos. Ari is a research scientist at Facebook AI Research (FAIR) in Menlo Park working on understanding the mechanisms underlying neural network computation and function, and using these insights to build machine learning systems more intelligently. In particular, he has worked on a variety of topics, including understanding the lottery tic...

Naila Murray - Interestingness predictions and getting to grips with data privacy

Aug 14 • 01:08:52

This week we are joined by Naila Murray. Naila obtained a B.Sc. in Electrical Engineering from Princeton University in 2007. In 2012, she received her PhD from the Universitat Autonoma de Barcelona, in affiliation with the Computer Vision Center. She joined NAVER LABS Europe (then Xerox Research Centre Europe) in January 2013, working on topics including fine-grained visua...

Julius Adebayo - Understanding a microprocessor and the evolution of hardware

Aug 7 • 01:10:42

This week we are joined by Julius Adebayo. Julius is a CS PhD student at MIT, interested in safe deployment of ML based systems as it relates to privacy/security, interpretability, fairness and robustness....

Anna Huang - Metaphor generation and ML for child welfare

Jul 22 • 01:13:38

We open season two of Underrated ML with Anna Huang on the show. Anna Huang is a Research Scientist at Google Brain, working on the Magenta project. Her research focuses on designing generative models to make creating music more approachable. She is the creator of Music Transformer and also the ML model Coconet that powered Google’s first AI Doodle the Bach Doodle....

Stephen Merity - Strongly typed RNNs and morphogenesis

Jun 23 • 01:33:49

We conclude season one of Underrated ML by having Stephen Merity on as our guest. Stephen has worked at various institutions such as MetaMind and Salesforce ohana, Google Sydney,, the Schwa Lab at the University of Sydney, the team at Grok Learning, the non-profit Common Crawl, and IACS @ Harvard. He also holds a Bachelor of Information Technology from the U...

Sebastian Ruder - Language independence and material properties

Jun 15 • 01:34:05

This week we are joined by Sebastian Ruder. He is a research scientist at DeepMind, London. He has also worked at a variety of institutions such as AYLIEN, Microsoft, IBM's Extreme Blue, Google Summer of Code, and SAP. These experiences were completed in tangent with his studies which included studying Computational Linguistics at the University of Heidelberg, Germany and ...

Kyunghyun Cho - Energy functions and shortcut learning

May 11 • 01:29:04

This week we are joined by Kyunghyun Cho. He is an associate professor of computer science and data science at New York University, a research scientist at Facebook AI Research and a CIFAR Associate Fellow. On top of this he also co-chaired the recent ICLR 2020 virtual conference....

Pooling Layers and learning from Brains

Apr 12 • 01:22:01

This week we take a look at the need for pooling layers within CNNs as well as discussing the regularization of CNNs using large-scale neuroscience data.

We are also very pleased to have Rosanne Liu join us on the show. Rosanne is a senior research scientist and a founding member of Uber AI. She is interested in making neural networks a better place and also currently runs ...

Abstract Reasoning and Peer Reviews

Mar 31 • 01:15:07

This weeks episode we take a look at Abstract Reasoning within Neural Networks as well as discussing the current review system surrounding ML papers. 

We are also very happy to have Jacob Buckman join us on the podcast this week. Jacob is currently undertaking a PhD at Mila having previously been a researcher at Google Brain with Sara Hooker. His main research interests lie...

Underrated ML - Xenobots and Critical Learning Periods

Mar 10 • 01:05:26

Have a listen to the first ever Underrated ML podcast! We'll walk you through two papers which we found really interesting followed by a few questions and then finally finishing with our verdict on what we believe was the most underrated paper!

Links to the papers can be found below.

Critical Learning Periods in Deep Neural Networks -

A scalab...

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