Artwork

The Thesis Review and Sean Welleck에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 The Thesis Review and Sean Welleck 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Player FM -팟 캐스트 앱
Player FM 앱으로 오프라인으로 전환하세요!

[12] Martha White - Regularized Factor Models

1:08:35
 
공유
 

Manage episode 302418433 series 2982803
The Thesis Review and Sean Welleck에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 The Thesis Review and Sean Welleck 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Martha White is an Associate Professor at the University of Alberta. Her research focuses on developing reinforcement learning and representation learning techniques for adaptive, autonomous agents learning on streams of data. Her PhD thesis is titled "Regularized Factor Models", which she completed in 2014 at the University of Alberta. We discuss the regularized factor model framework, which unifies many machine learning methods and led to new algorithms and applications. We talk about sparsity and how it also appears in her later work, as well as the common threads between her thesis work and her research in reinforcement learning. Episode notes: https://cs.nyu.edu/~welleck/episode12.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview
  continue reading

47 에피소드

Artwork
icon공유
 
Manage episode 302418433 series 2982803
The Thesis Review and Sean Welleck에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 The Thesis Review and Sean Welleck 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Martha White is an Associate Professor at the University of Alberta. Her research focuses on developing reinforcement learning and representation learning techniques for adaptive, autonomous agents learning on streams of data. Her PhD thesis is titled "Regularized Factor Models", which she completed in 2014 at the University of Alberta. We discuss the regularized factor model framework, which unifies many machine learning methods and led to new algorithms and applications. We talk about sparsity and how it also appears in her later work, as well as the common threads between her thesis work and her research in reinforcement learning. Episode notes: https://cs.nyu.edu/~welleck/episode12.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview
  continue reading

47 에피소드

Όλα τα επεισόδια

×
 
Loading …

플레이어 FM에 오신것을 환영합니다!

플레이어 FM은 웹에서 고품질 팟캐스트를 검색하여 지금 바로 즐길 수 있도록 합니다. 최고의 팟캐스트 앱이며 Android, iPhone 및 웹에서도 작동합니다. 장치 간 구독 동기화를 위해 가입하세요.

 

빠른 참조 가이드