New Directions in Multiple Kernel Learning

New Directions in Multiple Kernel Learning

15 Videos · 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/

Videos

Invited Speakers

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21:39

A Gaussian Process View on MKL

Raquel Urtasun

Jan 12, 2011

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11145 views

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35:21

Various Formulations for Learning the Kernel and Structured Sparsity

Massimiliano Pontil

Jan 12, 2011

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4208 views

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31:20

Structured Regularization for MKL

Guillaume Obozinski

Jan 12, 2011

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3642 views

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25:37

Distance Metric Learning for Kernel Machines

Kilian Q. Weinberger

Jan 12, 2011

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8680 views

Lectures

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16:34

Multitask Multiple Kernel Learning (MT-MKL)

Christian Widmer

Jan 12, 2011

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4585 views

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16:06

Online MKL for Structured Prediction

André F. T. Martins

Jan 12, 2011

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3619 views

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15:07

Co-regularized Spectral Clustering with Multiple Kernels

Piyush Rai

Jan 12, 2011

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4691 views

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19:10

Multiple Gaussian Process Models

Cedric Archambeau

Jan 12, 2011

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4878 views

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16:49

Regularization Strategies and Empirical Bayesian Learning for MKL

Ryota Tomioka

Jan 12, 2011

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5187 views

Poster Spotlights

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03:26

Learning Kernels via Margin-and-Radius Ratios

Kun Gai

Jan 12, 2011

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3444 views

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03:26

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

Ethem Alpaydin

Jan 12, 2011

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4050 views

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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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5812 views

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02:53

Multiple Kernel Learning for Efficient Conformal Predictions

Shayok Chakraborty

Jan 12, 2011

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3494 views

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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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3422 views

Panel discussion

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25:11

Panel discussion

Kilian Q. Weinberger,

Guillaume Obozinski,

Massimiliano Pontil,

Raquel Urtasun

Jan 26, 2011

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3580 views