Machine Learning Summer School (MLSS), Chicago 2005
40 Videos · May 15, 2005
About
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.
Videos
Introduction
Welcome
Apr 19, 2007 4135 views
Welcome to Chicago, and a (brief!) introduction to machine learning
Feb 25, 2007 5889 views
Lectures
Diffusion Maps, Spectral Clustering and Reaction Coordinates of Dynamical System...
Feb 25, 2007 10937 views
Empirical Comparisons of Learning Methods & Case Studies
Feb 25, 2007 6185 views
Game Dynamics with Learning and Evolution of Universal Grammar
Feb 25, 2007 3307 views
Online Learning with Kernels
Feb 25, 2007 7131 views
Categorical Perception + Linear Learning = Shared Culture
Feb 25, 2007 3549 views
The Dynamics of AdaBoost
Feb 25, 2007 24773 views
Learning on Structured Data
Feb 25, 2007 11801 views
On the Borders of Statistics and Computer Science
Feb 25, 2007 14056 views
Some Aspects of Learning Rates for SVMs
Feb 25, 2007 5771 views
Semi-supervised Learning, Manifold Methods
Feb 25, 2007 16500 views
Evidence Integration in Bioinformatics
Feb 25, 2007 5150 views
Bayesian Learning
Feb 25, 2007 41428 views
Adventures with Camille
Feb 25, 2007 4360 views
Learning variable covariances via gradients
Feb 25, 2007 3763 views
Energy-based models & Learning for Invariant Image Recognition
Feb 25, 2007 13319 views
Fingerprints of Rhthm in Natural Language
Feb 25, 2007 3506 views
Algorithms for Learning and their Estimates
Feb 25, 2007 3805 views
Feasible Language Learning
Feb 25, 2007 3547 views
An introduction to grammars and parsing
Feb 25, 2007 10508 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 14777 views
Learning on Structured Data
Feb 25, 2007 3989 views
On Optimal Estimators in Learning Theory
Feb 25, 2007 3667 views
Learning patterns in omic data: applications of learning theory
Feb 25, 2007 4478 views
On the evolution of languages
Feb 25, 2007 3720 views
Learning to Signal
Feb 25, 2007 3960 views
Multiscale analysis on graphs
Feb 25, 2007 4625 views
Trees for Regression and Classification
Feb 25, 2007 10470 views
Information Geometry
Feb 25, 2007 35683 views
Generalization bounds
Feb 25, 2007 8712 views
Semi-supervised Learning, Manifold Methods
Feb 25, 2007 9208 views
Introduction to Kernel Methods
Feb 25, 2007 17949 views
Interviews with students
Short interviews MLSS05 Chicago by John Langford
Feb 25, 2007 6525 views
Debates
Lunch debate 23.5.2005
Feb 25, 2007 6894 views
Lunch debate 25.5.2005
Feb 25, 2007 5531 views
Lunch debate 27.5.2005
Feb 25, 2007 3685 views
Lunch debate 24.5.2005
Feb 25, 2007 5213 views