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CORR
2010
Springer
127views Education» more  CORR 2010»
13 years 10 months ago
Mean field for Markov Decision Processes: from Discrete to Continuous Optimization
We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
Nicolas Gast, Bruno Gaujal, Jean-Yves Le Boudec
IROS
2008
IEEE
191views Robotics» more  IROS 2008»
14 years 4 months ago
Local Gaussian process regression for real-time model-based robot control
— High performance and compliant robot control requires accurate dynamics models which cannot be obtained analytically for sufficiently complex robot systems. In such cases, mac...
Duy Nguyen-Tuong, Jan Peters
RSS
2007
159views Robotics» more  RSS 2007»
13 years 11 months ago
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders
— In probabilistic mobile robotics, the development of measurement models plays a crucial role as it directly influences the efficiency and the robustness of the robot’s perf...
Christian Plagemann, Kristian Kersting, Patrick Pf...
ICDE
2005
IEEE
240views Database» more  ICDE 2005»
14 years 11 months ago
Adaptive Processing of Top-K Queries in XML
The ability to compute top-k matches to XML queries is gaining importance due to the increasing number of large XML repositories. The efficiency of top-k query evaluation relies o...
Amélie Marian, Divesh Srivastava, Nick Koud...
DCC
2004
IEEE
14 years 9 months ago
On the Entropy of a Hidden Markov Process
We study the entropy rate of a hidden Markov process (HMP) defined by observing the output of a binary symmetric channel whose input is a first-order binary Markov process. Despit...
Philippe Jacquet, Gadiel Seroussi, Wojciech Szpank...