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MLSS 2005 - Chicago   

Machine Learning Summer School (MLSS), Chicago 2005

Machine learning is a field focused on making machines learn to make predictions from examples. It combines elements of mathematics, computer science, and statistics with applications in biology, physics, engineering and any other area where automated prediction is necessary. This short summer school is an intense introduction to the basics of machine learning and learning theory with various additional advanced topics covered. It is appropriate for anyone interested in learning this material.

Categories

Introduction

[syn]  304 views, 35:49  
flagWelcomeWelcome
David McAllester, John Langford David McAllester, John Langford

Lectures

votesvotesvotesvotesvotes [syn]  15906 views, 2:07:12  
flagBoostingBoosting
Robert Schapire Robert Schapire
comments13 comments 
votesvotesvotesvotesvotes 7749 views, 1:24:46  
flagBayesian LearningBayesian Learning
Zoubin Ghahramani Zoubin Ghahramani
comments10 comments 

Interviews with students

Debates

votesvotesvotesvotesvotes 545 views, 1:23:45  
flagLunch debate 23.5.2005Lunch debate 23.5.2005
John Langford, David McAllester, et al. John Langford, David McAllester, Yasemin Altun, Yann LeCun, Zoubin Ghahramani, Sanjoy Dasgupta, Partha Niyogi
238 views, 25:46  
flagLunch debate 24.5.2005Lunch debate 24.5.2005
John Langford, Robert Schapire, et al. John Langford, Robert Schapire, Yann LeCun, Mikhail Belkin, Yoram Singer
159 views, 35:40  
flagLunch debate 25.5.2005Lunch debate 25.5.2005
John Langford, Yasemin Altun, et al. John Langford, Yasemin Altun, Yann LeCun, Yoram Singer, Robert Schapire, David McAllester
84 views, 14:39  
flagLunch debate 27.5.2005Lunch debate 27.5.2005
John Langford, Rich Caruana, et al. John Langford, Rich Caruana, Mikhail Belkin, Adam Kalai

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