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TSMC
2008
84views more  TSMC 2008»
15 years 4 months ago
Learning Inverse Kinematics: Reduced Sampling Through Decomposition Into Virtual Robots
We propose a technique to speedup the learning of the inverse kinematics of a robot manipulator by decomposing it into two or more virtual robot arms. Unlike previous decomposition...
Vicente Ruiz de Angulo, Carme Torras
158
Voted
TCBB
2010
137views more  TCBB 2010»
14 years 11 months ago
The Metropolized Partial Importance Sampling MCMC Mixes Slowly on Minimum Reversal Rearrangement Paths
Markov chain Monte Carlo has been the standard technique for inferring the posterior distribution of genome rearrangement scenarios under a Bayesian approach. We present here a neg...
István Miklós, Bence Melykuti, Krist...
AIPS
2011
14 years 8 months ago
Sample-Based Planning for Continuous Action Markov Decision Processes
In this paper, we present a new algorithm that integrates recent advances in solving continuous bandit problems with sample-based rollout methods for planning in Markov Decision P...
Christopher R. Mansley, Ari Weinstein, Michael L. ...
KBSE
2007
IEEE
15 years 11 months ago
Parseweb: a programmer assistant for reusing open source code on the web
Programmers commonly reuse existing frameworks or libraries to reduce software development efforts. One common problem in reusing the existing frameworks or libraries is that the...
Suresh Thummalapenta, Tao Xie
AI
2004
Springer
15 years 10 months ago
Distributed Data Mining vs. Sampling Techniques: A Comparison
To address the of mining a huge volume of geographically distributed databases, we propose two approaches. The first one is to download only a sample of each database. The second ...
Mohamed Aounallah, Sébastien Quirion, Guy W...