Machine Learning Summer School (MLSS), Taipei 2006

Machine Learning Summer School (MLSS), Taipei 2006

31 Lectures · Jul 23, 2006

About

The two-week summer school program consists of about 40+ hours of lectures from 7/24 to 8/4. The late afternoon sessions will provide a chance for the participants to discuss the latest research problems with the invited speakers. Prior to the summer school, the National Taiwan University of Science and Technology will offer a month-long machine learning summer course for graduate credits. You may choose part of them that fit your need or attend everything if you are sufficiently energetic.

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Lectures

02:29:08

Machine Learning Reductions

John Langford

Feb 25, 2007

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7698 Views

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32:18

Neighbourhood Components Analysis

Sam Roweis

Feb 25, 2007

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19665 Views

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36:31

Triple jump acceleration for the EM algorithm and its extrapolation-based varian...

Han-Shen Huang

Feb 25, 2007

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3702 Views

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02:15:42

Reinforcement Learning Theory

John Langford

Feb 25, 2007

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13378 Views

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36:48

Agnostic Active Learning

John Langford

Feb 25, 2007

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9808 Views

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17:26

Large-Margin Thresholded Ensembles for Ordinal Regression

Hsuan-Tien Lin

Feb 25, 2007

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7187 Views

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02:23:23

Predictive methods for Text mining

Tong Zhang

Feb 25, 2007

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8588 Views

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04:35:51

Graphical Models, Variational Methods, and Message-Passing

Martin J. Wainwright

Feb 25, 2007

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29906 Views

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36:10

Regularization of Kernel Methods by Decreasing the Bandwidth of the Gaussian Ker...

Jean-Philippe Vert

Jun 11, 2007

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6187 Views

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33:47

Large Scale Ranking Problem: some theoretical and algorithmic issues

Tong Zhang

Feb 25, 2007

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6420 Views

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15:07

Intel Research : User Activity based Adaptive Power Management (APM)

Nilesh Shah

Feb 25, 2007

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4095 Views

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22:06

Piecewise 1-Dim Self Organizing Map P1D-SOM

Alaa Sagheer

Feb 25, 2007

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3803 Views

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03:54:31

Support Vector Machines

Chih-Jen Lin

Feb 25, 2007

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165617 Views

Tutorial
04:08:15

Kernel Methods in Computational Biology

Jean-Philippe Vert

Feb 25, 2007

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14352 Views

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29:18

Ranking Individuals by Group Comparisons

Chih-Jen Lin

Feb 25, 2007

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5634 Views

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35:28

Protein Subcellular Localization Prediction Based on Compartment-Specific Biolog...

Chia-Yu Su

Feb 25, 2007

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5726 Views

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35:30

L1-based relaxations for sparsity recovery and graphical model selection in the ...

Martin J. Wainwright

Feb 25, 2007

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6268 Views

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03:32:45

Online Learning and Bregman Divergences

Manfred K. Warmuth

Feb 25, 2007

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11740 Views

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32:24

Unifying Divergence Minimization and Statistical Inference via Convex Duality

Alex Smola

Feb 25, 2007

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5484 Views

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13:02

Identifying Temporal Patterns and Key Players in Document Collections

Benyah Shaparenko

Feb 25, 2007

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4728 Views

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27:50

Facial expression recognition and emotion recognition from speech

Dragos Datcu

Feb 25, 2007

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15028 Views

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28:53

Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimensi...

Manfred K. Warmuth

Feb 25, 2007

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5403 Views

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39:02

Splice form prediction using Machine Learning

Gunnar Rätsch

Feb 25, 2007

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4803 Views

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19:41

Kernels on histograms through the transportation polytope

Marco Cuturi

Feb 25, 2007

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4910 Views

Lecture
05:09:40

Pattern Classification and Large Margin Classifiers

Peter L. Bartlett

Feb 25, 2007

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9535 Views

Tutorial
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03:39:05

Clustering - An overview

Marina Meila

Feb 25, 2007

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24136 Views

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03:44:15

Introduction to Boosting

Gunnar Rätsch

Feb 25, 2007

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15504 Views

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33:18

The stability of a good clustering

Marina Meila

Feb 25, 2007

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6000 Views

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38:04

A Bayesian Probability Calculus for Density Matrices

Manfred K. Warmuth

Feb 25, 2007

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7917 Views

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50:05

AdaBoost is Universally Consistent

Peter L. Bartlett

Feb 25, 2007

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8246 Views

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18:37

Ranking by Stealing Human Cycles

Tingfan Wu

Feb 25, 2007

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4686 Views

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