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
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4118 views
Welcome to Chicago, and a (brief!) introduction to machine learning
Feb 25, 2007
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5873 views
Lectures
Diffusion Maps, Spectral Clustering and Reaction Coordinates of Dynamical System...
Feb 25, 2007
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10912 views
Empirical Comparisons of Learning Methods & Case Studies
Feb 25, 2007
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6166 views
Game Dynamics with Learning and Evolution of Universal Grammar
Feb 25, 2007
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3288 views
Online Learning with Kernels
Feb 25, 2007
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7102 views
Categorical Perception + Linear Learning = Shared Culture
Feb 25, 2007
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3526 views
The Dynamics of AdaBoost
Feb 25, 2007
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24731 views
Learning on Structured Data
Feb 25, 2007
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11787 views
On the Borders of Statistics and Computer Science
Feb 25, 2007
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14036 views
Some Aspects of Learning Rates for SVMs
Feb 25, 2007
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5763 views
Semi-supervised Learning, Manifold Methods
Feb 25, 2007
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16452 views
Evidence Integration in Bioinformatics
Feb 25, 2007
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5137 views
Bayesian Learning
Feb 25, 2007
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41428 views
Adventures with Camille
Feb 25, 2007
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4352 views
Learning variable covariances via gradients
Feb 25, 2007
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3744 views
Energy-based models & Learning for Invariant Image Recognition
Feb 25, 2007
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13319 views
Fingerprints of Rhthm in Natural Language
Feb 25, 2007
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3498 views
Algorithms for Learning and their Estimates
Feb 25, 2007
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3795 views
Feasible Language Learning
Feb 25, 2007
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3537 views
An introduction to grammars and parsing
Feb 25, 2007
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10495 views
Tutorial on Machine Learning Reductions
Feb 25, 2007
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16463 views
Online Learning and Game Theory
Feb 25, 2007
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28927 views
Introduction to Kernel Methods
Feb 25, 2007
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14749 views
Learning on Structured Data
Feb 25, 2007
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3969 views
On Optimal Estimators in Learning Theory
Feb 25, 2007
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3641 views
Learning patterns in omic data: applications of learning theory
Feb 25, 2007
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4465 views
On the evolution of languages
Feb 25, 2007
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3700 views
Learning to Signal
Feb 25, 2007
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3951 views
Multiscale analysis on graphs
Feb 25, 2007
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4625 views
Trees for Regression and Classification
Feb 25, 2007
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10451 views
Information Geometry
Feb 25, 2007
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35567 views
Generalization bounds
Feb 25, 2007
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8668 views
Semi-supervised Learning, Manifold Methods
Feb 25, 2007
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9195 views
Introduction to Kernel Methods
Feb 25, 2007
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17897 views
Interviews with students
Short interviews MLSS05 Chicago by John Langford
Feb 25, 2007
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6506 views
Debates
Lunch debate 23.5.2005
Feb 25, 2007
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6871 views
Lunch debate 25.5.2005
Feb 25, 2007
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5469 views
Lunch debate 27.5.2005
Feb 25, 2007
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3669 views
Lunch debate 24.5.2005
Feb 25, 2007
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5186 views