Open House on Multi-Task and Complex Outputs Learning, London 2006

Open House on Multi-Task and Complex Outputs Learning, London 2006

18 Lectures · Jul 9, 2006

About

The Open House is part of the PASCAL's fifth thematic programme. This scientific programme brings together researchers around two themes:

  • learning tasks where the target is complex (i.e. large number of different predictions) but has structure (sequence, tree, graph) that can be utilized for learning effectively;
  • multi-task learning, where several dependent learning tasks are to be tackled at once.

In particular, we shall focus on the following research topics/issues.

Related categories

Uploaded videos:

Introductions

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07:54

Introduction

Feb 25, 2007

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5317 Views

Introduction

Lectures

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01:04:00

Inductive transfer via embeddings into a common feature space

Feb 25, 2007

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3359 Views

Lecture
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50:24

Multi-task feature learning

Feb 25, 2007

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7170 Views

Lecture
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19:38

Learning with structured inputs

Feb 25, 2007

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3382 Views

Lecture
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48:05

Estimation of gradients and coordinate covariation in classification

Feb 25, 2007

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4413 Views

Lecture
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36:15

Slow subspace learning from stationary processes

Feb 25, 2007

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3128 Views

Lecture
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56:25

Multitask learning: the Bayesian way

Feb 25, 2007

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6015 Views

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01:08:00

Top-down vs. bottom-up methods for hierarchical classification

Feb 25, 2007

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8345 Views

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01:20:01

Learning shared representations for object recognition

Feb 25, 2007

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9663 Views

Lecture
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55:51

Output kernel tree

Feb 25, 2007

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4558 Views

Lecture
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47:57

Efficient max-margin Markov learning via conditional gradient and probabilistic ...

Feb 25, 2007

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4328 Views

Lecture
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20:40

XML structure mapping

Feb 25, 2007

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5804 Views

Lecture
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01:03:55

Going beyond bag-of-words: dealing with a text as a graph of triples

Feb 25, 2007

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8726 Views

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31:47

Machine Learning for Sequential Data: A Comparative Study with Applications to N...

Feb 25, 2007

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6916 Views

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13:48

Learning Structured Outputs via Kernel Dependency Estimation and Stochastic Gram...

Feb 25, 2007

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3444 Views

Lecture
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24:56

How to Teach Support Vector Machine to Learn Vector Outputs

Feb 25, 2007

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6522 Views

Lecture
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50:05

Learning Nonparametric Priors from Multiple Tasks

Feb 25, 2007

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4391 Views

Lecture
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29:59

Targeted PDF Learning

Feb 25, 2007

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4862 Views

Lecture