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AAAI
2008
13 years 10 months ago
Bounding the False Discovery Rate in Local Bayesian Network Learning
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
Ioannis Tsamardinos, Laura E. Brown
RAS
2006
105views more  RAS 2006»
13 years 7 months ago
Reinforcement learning for quasi-passive dynamic walking of an unstable biped robot
A class of biped locomotion called Passive Dynamic Walking (PDW) has been recognized to be efficient in energy consumption and a key to understand human walking. Although PDW is s...
Kentarou Hitomi, Tomohiro Shibata, Yutaka Nakamura...
COMCOM
2004
112views more  COMCOM 2004»
13 years 7 months ago
Design and analysis of optimal adaptive de-jitter buffers
In order to transfer voice or some other application requiring real-time delivery over a packet network, we need a de-jitter buffer to eliminate delay jitters. An important design...
Gagan L. Choudhury, Robert G. Cole
IROS
2006
IEEE
120views Robotics» more  IROS 2006»
14 years 1 months ago
Learning from Nature to Build Intelligent Autonomous Robots
Information processing within autonomous robots should follow a biomimetic approach. In contrast to traditional approaches that make intensive use of accurate measurements, numeric...
Rainer Bischoff 0002, Volker Graefe
ICIDS
2010
Springer
13 years 5 months ago
Emohawk: Learning Virtual Characters by Doing
Emohawk is a narrative-based serious game designed to be a supportive tool for teaching basics of virtual agents development at universities and high-schools. Emohawk is built util...
Michal Bída, Cyril Brom