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157
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NIPS
2007
15 years 6 months ago
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learn...
Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon
AAAI
2006
15 years 6 months ago
An Iterative Algorithm for Solving Constrained Decentralized Markov Decision Processes
Despite the significant progress to extend Markov Decision Processes (MDP) to cooperative multi-agent systems, developing approaches that can deal with realistic problems remains ...
Aurélie Beynier, Abdel-Illah Mouaddib
AIPS
2006
15 years 6 months ago
Reusing and Building a Policy Library
Policy Reuse is a method to improve reinforcement learning with the ability to solve multiple tasks by building upon past problem solving experience, as accumulated in a Policy Li...
Fernando Fernández, Manuela M. Veloso
BDA
2003
15 years 6 months ago
Memory Requirements for Query Execution in Highly Constrained Devices
Pervasive computing introduces data management requirements that must be tackled in a growingvariety of lightweight computing devices. Personal folders on chip, networks of sensor...
Nicolas Anciaux, Luc Bouganim, Philippe Pucheral
140
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IJCAI
2003
15 years 6 months ago
Optimal Time-Space Tradeoff in Probabilistic Inference
Recursive Conditioning, RC, is an any-space algorithm lor exact inference in Bayesian networks, which can trade space for time in increments of the size of a floating point number...
David Allen, Adnan Darwiche