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» The art of multiprocessor programming
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SIGDIAL
2010
14 years 9 months ago
Sparse Approximate Dynamic Programming for Dialog Management
Spoken dialogue management strategy optimization by means of Reinforcement Learning (RL) is now part of the state of the art. Yet, there is still a clear mismatch between the comp...
Senthilkumar Chandramohan, Matthieu Geist, Olivier...
SIAMMAX
2010
123views more  SIAMMAX 2010»
14 years 6 months ago
Joint Spectral Characteristics of Matrices: A Conic Programming Approach
We propose a new approach to estimate the joint spectral radius and the joint spectral subradius of an arbitrary set of matrices. We first restrict our attention to matrices that ...
Vladimir Protasov, Raphaël M. Jungers, Vincen...
ICMLA
2010
14 years 9 months ago
Incremental Learning of Relational Action Rules
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Christophe Rodrigues, Pierre Gérard, C&eacu...
HIPS
1997
IEEE
15 years 4 months ago
Complexity and Performance in Parallel Programming Languages
Several parallel programming languages, libraries and environments have been developed to ease the task of writing programs for multiprocessors. Proponents of each approach often ...
Steven P. Vanderwiel, Daphna Nathanson, David J. L...
DYNAMO
2000
74views more  DYNAMO 2000»
15 years 1 months ago
A framework for remote dynamic program optimization
Dynamic program optimization allows programs to be generated that are highly tuned for a given environment and input data set. Optimization techniques can be applied and re-applie...
Michael Voss, Rudolf Eigenmann