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ATAL
2008
Springer
13 years 9 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
ICCV
2009
IEEE
15 years 9 days ago
A Global Perspective on MAP Inference for Low-Level Vision
In recent years the Markov Random Field (MRF) has become the de facto probabilistic model for low-level vision applications. However, in a maximum a posteriori (MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...
SIAMSC
2010
136views more  SIAMSC 2010»
13 years 2 months ago
A Krylov Method for the Delay Eigenvalue Problem
Abstract. The Arnoldi method is currently a very popular algorithm to solve large-scale eigenvalue problems. The main goal of this paper is to generalize the Arnoldi method to the ...
Elias Jarlebring, Karl Meerbergen, Wim Michiels
BMCBI
2007
143views more  BMCBI 2007»
13 years 7 months ago
An adaptive bin framework search method for a beta-sheet protein homopolymer model
Background: The problem of protein structure prediction consists of predicting the functional or native structure of a protein given its linear sequence of amino acids. This probl...
Alena Shmygelska, Holger H. Hoos
JMLR
2008
150views more  JMLR 2008»
13 years 7 months ago
Discriminative Learning of Max-Sum Classifiers
The max-sum classifier predicts n-tuple of labels from n-tuple of observable variables by maximizing a sum of quality functions defined over neighbouring pairs of labels and obser...
Vojtech Franc, Bogdan Savchynskyy