Learning from Multiple Sources

Learning from Multiple Sources

11 Videos · Dec 12, 2009

About

Learning from Multiple Sources with Applications to Robotics

Learning from multiple sources denotes the problem of jointly learning from a set of (partially) related learning problems / views / tasks. This general concept underlies several subfields receiving increasing interest from the machine learning community, which differ in terms of the assumptions made about the dependency structure between learning problems. In particular, the concept includes topics such as data fusion, transfer learning, multitask learning, multiview learning, and learning under covariate shift. Several approaches for inferring and exploiting complex relationships between data sources have been presented, including both generative and discriminative approaches.

The workshop will provide a unified forum for cutting edge research on learning from multiple sources; the workshop will examine the general concept, theory and methods, and will also examine robotics as a natural application domain for learning from multiple sources. The workshop will address methodological challenges in the different subtopics and further interaction between them. The intended audience is researchers working in fields of multi-modal learning, data fusion, and robotics.

The Workshop homepage can be found at http://www.dcs.gla.ac.uk/~srogers/lms09/index.htm

Videos

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22:21

Information Theoretic Kernel Integration

Yiming Ying

Jan 19, 2010

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3582 views

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15:45

Multi-Way, Multi-View Learning

Ilkka Huopaniemi

Jan 19, 2010

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4782 views

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59:23

Where's What? - Towards Semantic Mapping of Urban Environments

Ingmar Posner

Jan 19, 2010

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4340 views

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06:59

Poster Spotlights

Arman Melkumyan,

Amrish S. Kapoor,

Brenna D. Argall,

Bertrand Douillard,

Jesús Martínez-Gómez

Jan 19, 2010

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3958 views

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20:06

Multitask Learning Using Nonparametrically Learned Predictor Subspaces

Piyush Rai

Jan 19, 2010

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4435 views

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28:58

Discussion and Future Directions

Jan 19, 2010

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3095 views

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16:00

Learning CRF Models from Drill Rig Sensors for Autonomous Mining

Sildomar T. Monteiro

Jan 19, 2010

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5089 views

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21:20

Bayesian Localized Multiple Kernel Learning

C. Mario Christoudias

Jan 19, 2010

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3772 views

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56:09

Multi-Task Learning with Gaussian Processes with Applications to Robot Inverse D...

Chris Williams

Jan 19, 2010

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5085 views

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18:54

Domain Adaptation for Mobile Robot Navigation

David Bradley

Jan 19, 2010

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3911 views

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20:16

A Bayesian Approach to Occupancy Mapping with Uncertain Inputs

Simon T. O'Callaghan

Jan 19, 2010

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3855 views