May 15, 2005 
40 videos 
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.
Introduction
Welcome
Apr 19, 2007 4138 views
Welcome to Chicago, and a (brief!) introduction to machine learning
Feb 25, 2007 5894 views
Lectures
Diffusion Maps, Spectral Clustering and Reaction Coordinates of Dynamical System...
Feb 25, 2007 10941 views
Empirical Comparisons of Learning Methods & Case Studies
Feb 25, 2007 6188 views
Game Dynamics with Learning and Evolution of Universal Grammar
Feb 25, 2007 3311 views
Online Learning with Kernels
Feb 25, 2007 7137 views
Categorical Perception + Linear Learning = Shared Culture
Feb 25, 2007 3553 views
The Dynamics of AdaBoost
Feb 25, 2007 24780 views
Learning on Structured Data
Feb 25, 2007 11806 views
On the Borders of Statistics and Computer Science
Feb 25, 2007 14062 views
Some Aspects of Learning Rates for SVMs
Feb 25, 2007 5777 views
Semi-supervised Learning, Manifold Methods
Feb 25, 2007 16510 views
Evidence Integration in Bioinformatics
Feb 25, 2007 5153 views
Bayesian Learning
Feb 25, 2007 41428 views
Adventures with Camille
Feb 25, 2007 4363 views
Learning variable covariances via gradients
Feb 25, 2007 3767 views
Energy-based models & Learning for Invariant Image Recognition
Feb 25, 2007 13319 views
Fingerprints of Rhthm in Natural Language
Feb 25, 2007 3508 views
Algorithms for Learning and their Estimates
Feb 25, 2007 3808 views
Feasible Language Learning
Feb 25, 2007 3554 views
An introduction to grammars and parsing
Feb 25, 2007 10515 views
Tutorial on Machine Learning Reductions
Feb 25, 2007 16463 views
Online Learning and Game Theory
Feb 25, 2007 28927 views
Introduction to Kernel Methods
Feb 25, 2007 14788 views
Learning on Structured Data
Feb 25, 2007 3994 views
On Optimal Estimators in Learning Theory
Feb 25, 2007 3672 views
Learning patterns in omic data: applications of learning theory
Feb 25, 2007 4483 views
On the evolution of languages
Feb 25, 2007 3725 views
Learning to Signal
Feb 25, 2007 3963 views
Multiscale analysis on graphs
Feb 25, 2007 4625 views
Trees for Regression and Classification
Feb 25, 2007 10473 views
Information Geometry
Feb 25, 2007 35705 views
Generalization bounds
Feb 25, 2007 8717 views
Semi-supervised Learning, Manifold Methods
Feb 25, 2007 9211 views
Introduction to Kernel Methods
Feb 25, 2007 17955 views
Interviews with students
Short interviews MLSS05 Chicago by John Langford
Feb 25, 2007 6528 views
Debates
Lunch debate 23.5.2005
Feb 25, 2007 6897 views
Lunch debate 25.5.2005
Feb 25, 2007 5534 views
Lunch debate 27.5.2005
Feb 25, 2007 3689 views
Lunch debate 24.5.2005
Feb 25, 2007 5217 views