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TOMACS
2010
79views more  TOMACS 2010»
13 years 2 days ago
A stochastic approximation method with max-norm projections and its applications to the Q-learning algorithm
In this paper, we develop a stochastic approximation method to solve a monotone estimation problem and use this method to enhance the empirical performance of the Q-learning algor...
Sumit Kunnumkal, Huseyin Topaloglu
DCC
2011
IEEE
13 years 11 days ago
Some observations on HC-128
In this paper, we use linear approximations of the addition modulo 2n of three n-bit integers to identify linear approximations of g1, g2, the feedback functions of HC-128. This, i...
Subhamoy Maitra, Goutam Paul, Shashwat Raizada, Su...
MIA
2010
170views more  MIA 2010»
13 years 5 days ago
Linear intensity-based image registration by Markov random fields and discrete optimization
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...
DCC
2008
IEEE
14 years 5 months ago
Compressive-Projection Principal Component Analysis for the Compression of Hyperspectral Signatures
A method is proposed for the compression of hyperspectral signature vectors on severely resourceconstrained encoding platforms. The proposed technique, compressive-projection prin...
James E. Fowler
AUTOMATICA
2007
179views more  AUTOMATICA 2007»
13 years 5 months ago
Approximate bisimulation relations for constrained linear systems
In this paper, we define the notion of approximate bisimulation relation between two continuous systems. While exact bisimulation requires that the observations of two systems ar...
Antoine Girard, George J. Pappas