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JMLR
2008
209views more  JMLR 2008»
15 years 6 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
JAIR
2006
160views more  JAIR 2006»
15 years 6 months ago
Anytime Point-Based Approximations for Large POMDPs
The Partially Observable Markov Decision Process has long been recognized as a rich framework for real-world planning and control problems, especially in robotics. However exact s...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
JAIR
2006
120views more  JAIR 2006»
15 years 6 months ago
FluCaP: A Heuristic Search Planner for First-Order MDPs
We present a heuristic search algorithm for solving first-order Markov Decision Processes (FOMDPs). Our approach combines first-order state abstraction that avoids evaluating stat...
Steffen Hölldobler, Eldar Karabaev, Olga Skvo...
JAR
2006
99views more  JAR 2006»
15 years 6 months ago
An Integrated Approach to High Integrity Software Verification
Using automated reasoning techniques, we tackle the niche activity of proving that a program is free from run-time exceptions. Such a property is particularly valuable in high inte...
Andrew Ireland, Bill J. Ellis, Andrew Cook, Roderi...
CSL
2007
Springer
15 years 6 months ago
Partially observable Markov decision processes for spoken dialog systems
In a spoken dialog system, determining which action a machine should take in a given situation is a difficult problem because automatic speech recognition is unreliable and hence ...
Jason D. Williams, Steve Young
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