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AAAI
2012
13 years 6 months ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
CORR
2006
Springer
105views Education» more  CORR 2006»
15 years 4 months ago
Generalization error bounds in semi-supervised classification under the cluster assumption
We consider semi-supervised classification when part of the available data is unlabeled. These unlabeled data can be useful for the classification problem when we make an assumpti...
Philippe Rigollet
JASIS
2011
103views more  JASIS 2011»
14 years 11 months ago
Using global mapping to create more accurate document-level maps of research fields
We describe two general approaches to creating document-level maps of science. To create a local map one defines and directly maps a sample of data, such as all literature publish...
Richard Klavans, Kevin W. Boyack
ICRA
2010
IEEE
189views Robotics» more  ICRA 2010»
15 years 2 months ago
Affordable SLAM through the co-design of hardware and methodology
— Simultaneous localization and mapping (SLAM) is a prominent feature for autonomous robots operating in undefined environments. Applications areas such as consumer robotics app...
Stéphane Magnenat, Valentin Longchamp, Mich...
GI
2000
Springer
15 years 7 months ago
Taming the Tiger: How to Cope with Real Database Products in Transactional Federations for Internet Applications
Data consistency in transactional federations is a key requirement of advanced E-service applications on the Internet, such as electronic auctions or real-estate purchase. Federat...
Ralf Schenkel, Gerhard Weikum