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Multi-Task Learning of System Dynamics with Maximum Information Gain Jose F. Zubizarreta-Rodriguez and Fabio Ramos Australian Centre for Field Robotics, School of Information Technologies The University of Sydney, Austra
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Document Date: 2015-01-05 23:35:42

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File Size: 541,95 KB

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Company

Neural Information Processing Systems / Cambridge University Press / MIT Press / Rio Tinto / /

Country

Mexico / /

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Event

Reorganization / /

Facility

Prentice Hall / Carnegie Mellon University / Mine Automation / Victoria University of Wellington / Information Technologies The University of Sydney / /

IndustryTerm

search action-state strategy / on-line problems / real dynamic systems / machine learning algorithms / adaptive learning algorithms / higher dimensional dynamic systems / greedy algorithm / on-line learning / search strategy / autonomous systems / robotic systems / /

Organization

School of Computer Science / Victoria University of Wellington / Cambridge University / Fabio Ramos Australian Centre for Field Robotics / ARC Centre of Excellence / Secretariat of Public Education / University of Sydney / MIT / New South Wales State Government / Carnegie Mellon University / LQR MOGP / Australian Research Council / Rio Tinto Centre for Mine Automation / /

Person

Bt / Fabio Ramos / Jose F. Zubizarreta-Rodriguez / /

ProgrammingLanguage

Occam / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / /

Region

South Wales / /

Technology

machine learning algorithms / GPS / greedy algorithm / machine learning / simulation / adaptive learning algorithms / 2.4 GHz processor / /

SocialTag