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Machine Learning Summer School (MLSS), Chicago 2009

Machine Learning Summer School (MLSS), Chicago 2009

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/

Opening

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07:15

Welcome Speech at the MLSS 2009

Steve Smale,

Mikhail Belkin

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Tutorials

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02:32:57

Graphical Models and Applications

Yair Weiss

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02:49:05

Semi-Supervised Learning

Jerry (Xiaojin) Zhu

calendar icon Jul 30, 2009 22970 views

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03:05:36

Bounding Excess Risk in Machine Learning

Vladimir Koltchinskii

calendar icon Jul 30, 2009 7414 views

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02:49:58

Theory, Methods and Applications of Active Learning

Rui Castro,

Robert D. Nowak

calendar icon Jul 30, 2009 20708 views

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02:59:33

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

Emmanuel Candes

calendar icon Jul 30, 2009 79772 views

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03:01:09

Geometric Methods and Manifold Learning

Partha Niyogi,

Mikhail Belkin

calendar icon Jul 30, 2009 41026 views

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02:27:49

Analysis of Clustering Procedures

Sanjoy Dasgupta

calendar icon Jul 30, 2009 9765 views

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02:46:48

Kernel Methods and Support Vector Machines

John Shawe-Taylor

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02:42:23

Theory and Applications of Boosting

Robert Schapire

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Plenary Talks

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55:23

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

Grace Wahba

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58:41

Spectral Graph Theory, Linear Solvers and Applications

Gary L Miller

calendar icon Jul 30, 2009 8891 views

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47:29

Sparse Representations from Inverse Problems to Pattern Recognition

Stéphane Mallat

calendar icon Jul 30, 2009 14260 views

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59:29

Generative Models for Image Analysis

Stuart Geman

calendar icon Jul 30, 2009 6291 views

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45:52

Inference for Networks

Peter J. Bickel

calendar icon Jul 30, 2009 4522 views

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01:07:14

Matrix Completion via Convex Optimization: Theory and Algorithms

Emmanuel Candes

calendar icon Jul 30, 2009 24481 views

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01:10:11

Learning in Hierarchical Architectures: from Neuroscience to Derived Kernels

Tomaso A. Poggio

calendar icon Jul 30, 2009 9101 views

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51:33

The Stability of the Contour of an Orientable 2-Manifold

Herbert Edelsbrunner

calendar icon Jul 30, 2009 4129 views

Monday, June 1

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54:00

Geometric Inference for Probability Distribution

Frederic Chazal

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49:28

Cut Locus and Topology from Point Data

Tamal Dey

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01:00:47

PAC-Bayes Analysis: Background and Applications

John Shawe-Taylor

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Tuesday, June 2

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55:36

Euler Calculus and Topological Data Management

Robert Ghrist

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51:29

Learning Dictionaries for Image Analysis and Sensing

Guillermo Sapiro

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58:33

Seeking Interpretable Models for High Dimensional Data

Bin Yu

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Wednesday, June 3

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49:30

Vision and Hodge Theory

Stephen Smale

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50:43

Statistical Classification and Cluster Processes

Peter McCullagh

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55:19

Learning Deformable Models

Yali Amit

calendar icon Jul 30, 2009 5569 views

Thursday, June 4

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55:43

Optimization Algorithms in Support Vector Machines

Stephen J. Wright

calendar icon Jul 30, 2009 7230 views

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58:51

Learning Feature Hierarchies

Yann LeCun

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51:30

Unsupervised Learning for Stereo Vision

David McAllester

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Friday, June 5

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46:23

Similarity-Based Classifiers: Problems and Solutions

Maya Gupta

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01:02:06

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

Amit Singer

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59:22

On Surrogate Loss Functions, f-Divergences and Decentralized Detection

Michael I. Jordan

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Saturday, June 6

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44:40

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

Nathan Srebro

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47:48

On Finding Low Error Clusterings

Maria-Florina Balcan

calendar icon Jul 30, 2009 7676 views

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53:34

How to Visualize the Unseeable

Xiaochuan Pan

calendar icon Jul 30, 2009 3635 views

Monday, June 8

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59:17

Fitting a Graph to Vector Data

Daniel A. Spielman

calendar icon Jul 30, 2009 6093 views

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01:01:41

On a Theory of Similarity Functions for Learning and Clustering

Avrim Blum

calendar icon Jul 30, 2009 5281 views

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47:30

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

Yoonkyung Lee

calendar icon Jul 30, 2009 4513 views

Tuesday, June 9

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58:13

Multiscale Geometry and Harmonic Analysis of Data Bases

Ronald Coifman

calendar icon Jul 30, 2009 6268 views

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52:44

Cheeger Cuts and p-Spectral Clustering

Matthias Hein

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49:17

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

Karen Livescu

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Wednesday, June 10

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51:29

Drifting Games, Boosting and Online Learning

Yoav Freund

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54:38

MAP Estimation with Perfect Graphs

Tony Jebara

calendar icon Jul 30, 2009 5640 views

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38:46

Recent Progress in Combinatorial Statistics

Elchanan Mossel

calendar icon Jul 30, 2009 4325 views

Thursday, June 11

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57:29

Cocktail Party Problem as Binary Classification

DeLiang Wang

calendar icon Jul 30, 2009 6688 views

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54:54

Machine Learning in Acoustic Signal Processing

Mark Hasegawa-Johnson

calendar icon Jul 30, 2009 14107 views

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