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» Tackling Large State Spaces in Performance Modelling
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UAI
2008
13 years 10 months ago
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Richard S. Sutton, Csaba Szepesvári, Alborz...
SPIN
2000
Springer
14 years 16 days ago
Modeling the ASCB-D Synchronization Algorithm with SPIN: A Case Study
In this paper, we describe our application of SPIN 1 to model an algorithm used to synchronize the clocks of modules that provide periodic real-time communication over a network. W...
Nicholas Weininger, Darren D. Cofer
CVPR
2009
IEEE
15 years 4 months ago
Shared Kernel Information Embedding for Discriminative Inference
Latent Variable Models (LVM), like the Shared-GPLVM and the Spectral Latent Variable Model, help mitigate over- fitting when learning discriminative methods from small or modera...
David J. Fleet, Leonid Sigal, Roland Memisevic
DSP
2007
13 years 9 months ago
Variational and stochastic inference for Bayesian source separation
We tackle the general linear instantaneous model (possibly underdetermined and noisy) where we model the source prior with a Student t distribution. The conjugate-exponential char...
Ali Taylan Cemgil, Cédric Févotte, S...
ECCV
2010
Springer
14 years 2 months ago
Building Compact Local Pairwise Codebook with Joint Feature Space Clustering
Abstract. This paper presents a simple, yet effective method of building a codebook for pairs of spatially close SIFT descriptors. Integrating such codebook into the popular bag-o...