Machine Learning Summer School (MLSS), Chicago 2009

Machine Learning Summer School (MLSS), Chicago 2009

47 Lectures ยท Jun 1, 2009

About

The theme of this year's summer school is Theory and Practice of Computational Learning, to be held in conjunction with a research workshop on the same topic, during the period June 1-11, 2009 at International House, University of Chicago. The program will consist of a mixture of tutorial lectures and research talks. 3-4 hours of tutorial lectures will be held in the morning, and the reserarch talks in the afternoon.


The Summer school homepage can be found at http://www.cse.ohio-state.edu/mlss09/

Related categories

Uploaded videos:

Opening

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07:15

Welcome Speech at the MLSS 2009

Steve Smale,

Mikhail Belkin

Jul 30, 2009

 ยท 

4825 Views

Opening

Tutorials

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02:46:48

Kernel Methods and Support Vector Machines

John Shawe-Taylor

Jul 30, 2009

 ยท 

17119 Views

Tutorial
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02:32:57

Graphical Models and Applications

Yair Weiss

Jul 30, 2009

 ยท 

13461 Views

Tutorial
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03:01:09

Geometric Methods and Manifold Learning

Partha Niyogi,

Mikhail Belkin

Jul 30, 2009

 ยท 

40819 Views

Tutorial
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02:49:58

Theory, Methods and Applications of Active Learning

Robert D. Nowak,

Rui Castro

Jul 30, 2009

 ยท 

20633 Views

Tutorial
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02:42:23

Theory and Applications of Boosting

Robert Schapire

Jul 30, 2009

 ยท 

24200 Views

Lecture
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03:05:36

Bounding Excess Risk in Machine Learning

Vladimir Koltchinskii

Jul 30, 2009

 ยท 

7350 Views

Tutorial
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02:27:49

Analysis of Clustering Procedures

Sanjoy Dasgupta

Jul 30, 2009

 ยท 

9699 Views

Tutorial
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02:59:33

An Overview of Compressed Sensing and Sparse Signal Recovery via L1 Minimization

Emmanuel Candes

Jul 30, 2009

 ยท 

79569 Views

Tutorial
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02:49:05

Semi-Supervised Learning

Jerry (Xiaojin) Zhu

Jul 30, 2009

 ยท 

22902 Views

Tutorial

Plenary Talks

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55:23

Examining the Relative Influence of Familial, Genetic, and Environmental Covaria...

Grace Wahba

Jul 30, 2009

 ยท 

4218 Views

Invited Talk
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47:29

Sparse Representations from Inverse Problems to Pattern Recognition

Stรฉphane Mallat

Jul 30, 2009

 ยท 

14238 Views

Invited Talk
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59:29

Generative Models for Image Analysis

Stuart Geman

Jul 30, 2009

 ยท 

6265 Views

Invited Talk
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01:10:11

Learning in Hierarchical Architectures: from Neuroscience to Derived Kernels

Tomaso A. Poggio

Jul 30, 2009

 ยท 

9063 Views

Invited Talk
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51:33

The Stability of the Contour of an Orientable 2-Manifold

Herbert Edelsbrunner

Jul 30, 2009

 ยท 

4102 Views

Invited Talk
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58:41

Spectral Graph Theory, Linear Solvers and Applications

Gary L Miller

Jul 30, 2009

 ยท 

8852 Views

Invited Talk
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01:07:14

Matrix Completion via Convex Optimization: Theory and Algorithms

Emmanuel Candes

Jul 30, 2009

 ยท 

24384 Views

Invited Talk
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45:52

Inference for Networks

Peter J. Bickel

Jul 30, 2009

 ยท 

4496 Views

Invited Talk

Monday, June 1

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54:00

Geometric Inference for Probability Distribution

Frederic Chazal

Jul 30, 2009

 ยท 

5292 Views

Lecture
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01:00:47

PAC-Bayes Analysis: Background and Applications

John Shawe-Taylor

Jul 30, 2009

 ยท 

5847 Views

Lecture
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49:28

Cut Locus and Topology from Point Data

Tamal Dey

Jul 30, 2009

 ยท 

5082 Views

Lecture

Tuesday, June 2

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55:36

Euler Calculus and Topological Data Management

Robert Ghrist

Jul 30, 2009

 ยท 

7131 Views

Lecture
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58:33

Seeking Interpretable Models for High Dimensional Data

Bin Yu

Jul 30, 2009

 ยท 

6317 Views

Lecture
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51:29

Learning Dictionaries for Image Analysis and Sensing

Guillermo Sapiro

Jul 30, 2009

 ยท 

15778 Views

Lecture

Wednesday, June 3

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49:30

Vision and Hodge Theory

Stephen Smale

Jul 30, 2009

 ยท 

5893 Views

Lecture
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55:19

Learning Deformable Models

Yali Amit

Jul 30, 2009

 ยท 

5550 Views

Lecture
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50:43

Statistical Classification and Cluster Processes

Peter McCullagh

Jul 30, 2009

 ยท 

4833 Views

Lecture

Thursday, June 4

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55:43

Optimization Algorithms in Support Vector Machines

Stephen J. Wright

Jul 30, 2009

 ยท 

7163 Views

Lecture
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51:30

Unsupervised Learning for Stereo Vision

David McAllester

Jul 30, 2009

 ยท 

6151 Views

Lecture
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58:51

Learning Feature Hierarchies

Yann LeCun

Jul 30, 2009

 ยท 

9476 Views

Lecture

Friday, June 5

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59:22

On Surrogate Loss Functions, f-Divergences and Decentralized Detection

Michael I. Jordan

Jul 30, 2009

 ยท 

8832 Views

Lecture
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46:23

Similarity-Based Classifiers: Problems and Solutions

Maya Gupta

Jul 30, 2009

 ยท 

5592 Views

Lecture
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01:02:06

What Do Unique Games, Structural Biology and the Low-Rank Matrix Completion Prob...

Amit Singer

Jul 30, 2009

 ยท 

6172 Views

Lecture

Saturday, June 6

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44:40

More Data Less Work: Runtime As A Monotonically Decreasing Function of Data Set ...

Nathan Srebro

Jul 30, 2009

 ยท 

4045 Views

Lecture
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47:48

On Finding Low Error Clusterings

Maria-Florina Balcan

Jul 30, 2009

 ยท 

7640 Views

Lecture
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53:34

How to Visualize the Unseeable

Xiaochuan Pan

Jul 30, 2009

 ยท 

3602 Views

Lecture

Monday, June 8

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01:01:41

On a Theory of Similarity Functions for Learning and Clustering

Avrim Blum

Jul 30, 2009

 ยท 

5255 Views

Lecture
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47:30

A Bahadur Type Representation of the Linear Support Vector Machine and its Relat...

Yoonkyung Lee

Jul 30, 2009

 ยท 

4477 Views

Lecture
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59:17

Fitting a Graph to Vector Data

Daniel A. Spielman

Jul 30, 2009

 ยท 

6065 Views

Lecture

Tuesday, June 9

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52:44

Cheeger Cuts and p-Spectral Clustering

Matthias Hein

Jul 30, 2009

 ยท 

5642 Views

Lecture
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58:13

Multiscale Geometry and Harmonic Analysis of Data Bases

Ronald Coifman

Jul 30, 2009

 ยท 

6217 Views

Lecture
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49:17

Graphical Models for Speech Recognition: Articulatory and Audio-Visual Models

Karen Livescu

Jul 30, 2009

 ยท 

7157 Views

Lecture

Wednesday, June 10

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51:29

Drifting Games, Boosting and Online Learning

Yoav Freund

Jul 30, 2009

 ยท 

5398 Views

Lecture
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38:46

Recent Progress in Combinatorial Statistics

Elchanan Mossel

Jul 30, 2009

 ยท 

4296 Views

Lecture
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54:38

MAP Estimation with Perfect Graphs

Tony Jebara

Jul 30, 2009

 ยท 

5605 Views

Lecture

Thursday, June 11

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57:29

Cocktail Party Problem as Binary Classification

DeLiang Wang

Jul 30, 2009

 ยท 

6659 Views

Lecture
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54:54

Machine Learning in Acoustic Signal Processing

Mark Hasegawa-Johnson

Jul 30, 2009

 ยท 

14071 Views

Lecture