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CIE
2007
Springer
14 years 1 months ago
Computational Complexity of Constraint Satisfaction
Abstract. The input to a constraint satisfaction problem (CSP) consists of a set of variables, each with a domain, and constraints between these variables formulated by relations o...
Heribert Vollmer
ML
2008
ACM
152views Machine Learning» more  ML 2008»
13 years 7 months ago
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
András Antos, Csaba Szepesvári, R&ea...
JAIR
2000
152views more  JAIR 2000»
13 years 7 months ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
ICALP
2009
Springer
14 years 7 months ago
Functional Monitoring without Monotonicity
The notion of distributed functional monitoring was recently introduced by Cormode, Muthukrishnan and Yi [CMY08] to initiate a formal study of the communication cost of certain fu...
Chrisil Arackaparambil, Joshua Brody, Amit Chakrab...
JMIV
2010
98views more  JMIV 2010»
13 years 6 months ago
Expectations of Random Sets and Their Boundaries Using Oriented Distance Functions
Shape estimation and object reconstruction are common problems in image analysis. Mathematically, viewing objects in the image plane as random sets reduces the problem of shape es...
Hanna K. Jankowski, Larissa I. Stanberry