New Directions in Multiple Kernel Learning

New Directions in Multiple Kernel Learning

15 Lectures · Dec 10, 2010

About

Research on Multiple Kernel Learning (MKL) has matured to the point where efficient systems can be applied out of the box to various application domains. In contrast to last year’s workshop, which evaluated the achievements of MKL in the past decade, this workshop looks beyond the standard setting and investigates new directions for MKL. In particular, we focus on two topics:

There are three research areas, which are closely related, but have traditionally been treated separately: learning the kernel, learning distance metrics, and learning the

covariance function of a Gaussian process. We therefore would like to bring together researchers from these areas to find a unifying view, explore connections, and exchange ideas.

We ask for novel contributions that take new directions, propose

innovative approaches, and take unconventional views. This includes research, which goes beyond the limited classical sumof- kernels setup, finds new ways of combining kernels, or applies MKL in more complex settings.

Taking advantage of the broad variety of research topics at NIPS, the workshop aims to foster collaboration across the borders of the traditional multiple kernel learning community.

Workshop homepage: http://doc.ml.tu-berlin.de/mkl_workshop/

Related categories

Uploaded videos:

Invited Speakers

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35:21

Various Formulations for Learning the Kernel and Structured Sparsity

Massimiliano Pontil

Jan 12, 2011

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4202 Views

Invited Talk
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21:39

A Gaussian Process View on MKL

Raquel Urtasun

Jan 12, 2011

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11119 Views

Invited Talk
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31:20

Structured Regularization for MKL

Guillaume Obozinski

Jan 12, 2011

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3638 Views

Invited Talk
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25:37

Distance Metric Learning for Kernel Machines

Kilian Q. Weinberger

Jan 12, 2011

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8677 Views

Invited Talk

Lectures

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16:49

Regularization Strategies and Empirical Bayesian Learning for MKL

Ryota Tomioka

Jan 12, 2011

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5181 Views

Lecture
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16:06

Online MKL for Structured Prediction

André F. T. Martins

Jan 12, 2011

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3617 Views

Lecture
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19:10

Multiple Gaussian Process Models

Cedric Archambeau

Jan 12, 2011

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4869 Views

Lecture
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16:34

Multitask Multiple Kernel Learning (MT-MKL)

Christian Widmer

Jan 12, 2011

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4579 Views

Lecture
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15:07

Co-regularized Spectral Clustering with Multiple Kernels

Piyush Rai

Jan 12, 2011

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4681 Views

Lecture

Poster Spotlights

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03:26

Supervised and Localized Dimensionality Reduction from Multiple Feature Represen...

Ethem Alpaydin

Jan 12, 2011

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4045 Views

Poster
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02:53

Multiple Kernel Learning for Efficient Conformal Predictions

Shayok Chakraborty

Jan 12, 2011

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3490 Views

Poster
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03:26

Operator Induced Multi-Task Gaussian Processes for Solving Differential Equation...

Arman Melkumyan

Jan 12, 2011

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3417 Views

Poster
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03:26

Learning Kernels via Margin-and-Radius Ratios

Kun Gai

Jan 12, 2011

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3440 Views

Poster
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03:52

Currency Forecasting using Multiple Kernel Learning with Financially Motivated F...

Tristan Fletcher

Jan 12, 2011

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5810 Views

Poster

Panel discussion

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25:11

Panel discussion

Massimiliano Pontil,

Raquel Urtasun,

Kilian Q. Weinberger,

Guillaume Obozinski

Jan 26, 2011

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3575 Views

Debate