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

Top » Computer Science » Machine Learning


Introduction
[syn] 4101 views, 35:49 WelcomeWelcome David McAllester, John Langford David McAllester, John Langford	[syn] 5857 views, 12:40 Welcome to Chicago, and a (brief!) introduction to machine learningWelcome to Chicago, and a (brief!) introduction to machine learning John Langford John Langford
Lectures
[syn] 28927 views, 1:37:46 Online Learning and Game TheoryOnline Learning and Game Theory Adam Kalai Adam Kalai 6 comments	[syn] 8608 views, 1:42:36 Generalization boundsGeneralization bounds John Langford John Langford	[syn] 14733 views, 1:00:54 Introduction to Kernel MethodsIntroduction to Kernel Methods Mikhail Belkin Mikhail Belkin	[syn] 16393 views, 47:32 Semi-supervised Learning, Manifold MethodsSemi-supervised Learning, Manifold Methods Mikhail Belkin Mikhail Belkin	[syn] 17840 views, 1:21:57 Introduction to Kernel MethodsIntroduction to Kernel Methods Partha Niyogi Partha Niyogi 5 comments
[syn] 9174 views, 54:52 Semi-supervised Learning, Manifold MethodsSemi-supervised Learning, Manifold Methods Partha Niyogi Partha Niyogi 1 comment	[syn] 5126 views, 1:04:59 Evidence Integration in BioinformaticsEvidence Integration in Bioinformatics Phil Long Phil Long	[syn] 6153 views, 2:01:19 Empirical Comparisons of Learning Methods & Case StudiesEmpirical Comparisons of Learning Methods & Case Studies Rich Caruana Rich Caruana	[syn] 88683 views, 2:07:12 BoostingBoosting Robert Schapire Robert Schapire 13 comments	[syn] 10426 views, 21:44 Trees for Regression and ClassificationTrees for Regression and Classification Robert D. Nowak Robert D. Nowak
[syn] 3783 views, 49:49 Algorithms for Learning and their EstimatesAlgorithms for Learning and their Estimates Steve Smale Steve Smale	[syn] 13319 views, 3:38:44 Energy-based models & Learning for Invariant Image RecognitionEnergy-based models & Learning for Invariant Image Recognition Yann LeCun Yann LeCun 10 comments	[syn] 7086 views, 1:23:27 Online Learning with KernelsOnline Learning with Kernels Yoram Singer Yoram Singer 1 comment	[syn] 3491 views, 53:58 Fingerprints of Rhthm in Natural LanguageFingerprints of Rhthm in Natural Language Antonio Galves Antonio Galves	[syn] 10874 views, 55:35 Diffusion Maps, Spectral Clustering and Reaction Coordinates of Dynamical SystemsDiffusion Maps, Spectral Clustering and Reaction Coordinates of Dynamical Systems Boaz Nadler Boaz Nadler 5 comments
[syn] 3941 views, 50:51 Learning to SignalLearning to Signal Brian Skyrms Brian Skyrms	[syn] 24685 views, 32:36 The Dynamics of AdaBoostThe Dynamics of AdaBoost Cynthia Rudin Cynthia Rudin 3 comments	[syn] 3734 views, 53:01 Learning variable covariances via gradientsLearning variable covariances via gradients Ding-Xuan Zhou Ding-Xuan Zhou	[syn] 3526 views, 1:05:34 Feasible Language LearningFeasible Language Learning Ed Stabler Ed Stabler	[syn] 3687 views, 1:10:31 On the evolution of languagesOn the evolution of languages Felipe Cucker Felipe Cucker
[syn] 3268 views, 55:17 Game Dynamics with Learning and Evolution of Universal GrammarGame Dynamics with Learning and Evolution of Universal Grammar Garrett Mitchener Garrett Mitchener	[syn] 5751 views, 56:08 Some Aspects of Learning Rates for SVMsSome Aspects of Learning Rates for SVMs Ingo Steinwart Ingo Steinwart	[syn] 3510 views, 51:40 Categorical Perception + Linear Learning = Shared CultureCategorical Perception + Linear Learning = Shared Culture Mark Liberman Mark Liberman	4625 views, 58:48 Multiscale analysis on graphsMultiscale analysis on graphs Mauro Maggioni Mauro Maggioni	[syn] 4340 views, 53:48 Adventures with CamilleAdventures with Camille Peter Culicover Peter Culicover
[syn] 3623 views, 51:50 On Optimal Estimators in Learning TheoryOn Optimal Estimators in Learning Theory Vladimir Temlyakov Vladimir Temlyakov	[syn] 16463 views, 2:38:48 Tutorial on Machine Learning ReductionsTutorial on Machine Learning Reductions John Langford John Langford 3 comments	[syn] 35444 views, 1:35:21 Information GeometryInformation Geometry Sanjoy Dasgupta Sanjoy Dasgupta 4 comments	[syn] 14011 views, 59:35 On the Borders of Statistics and Computer ScienceOn the Borders of Statistics and Computer Science Peter J. Bickel Peter J. Bickel 1 comment	[syn] 41428 views, 1:24:46 Bayesian LearningBayesian Learning Zoubin Ghahramani Zoubin Ghahramani 10 comments
[syn] 3942 views, 1:44:36 Learning on Structured DataLearning on Structured Data David McAllester David McAllester 1 comment	[syn] 11756 views, 1:16:33 Learning on Structured DataLearning on Structured Data Yasemin Altun Yasemin Altun 2 comments	[syn] 10455 views, 1:24:18 An introduction to grammars and parsingAn introduction to grammars and parsing Mark Johnson Mark Johnson 8 comments	[syn] 4441 views, 41:36 Learning patterns in omic data: applications of learning theoryLearning patterns in omic data: applications of learning theory Sayan Mukherjee Sayan Mukherjee
Interviews with students
[syn] 6480 views, 04:16 Short interviews MLSS05 Chicago by John LangfordShort interviews MLSS05 Chicago by John Langford John Langford John Langford
Debates
[syn] 6857 views, 1:23:45 Lunch 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	[syn] 5146 views, 25:46 Lunch debate 24.5.2005Lunch debate 24.5.2005 John Langford, Robert Schapire, et al. John Langford, Robert Schapire, Yann LeCun, Mikhail Belkin, Yoram Singer 1 comment	[syn] 5453 views, 35:40 Lunch 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 1 comment	[syn] 3660 views, 14:39 Lunch debate 27.5.2005Lunch debate 27.5.2005 John Langford, Rich Caruana, et al. John Langford, Rich Caruana, Mikhail Belkin, Adam Kalai