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» Providing Automatic Support for Heuristic Rules of Methods
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NIPS
2008
14 years 11 months ago
Hebbian Learning of Bayes Optimal Decisions
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
JAIR
2000
152views more  JAIR 2000»
14 years 9 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
CICLING
2005
Springer
15 years 3 months ago
Incremental Information Extraction Using Tree-Based Context Representations
Abstract. The purpose of information extraction (IE) is to find desired pieces of information in natural language texts and store them in a form that is suitable for automatic pro...
Christian Siefkes
KBSE
1999
IEEE
15 years 2 months ago
Modular and Incremental Analysis of Concurrent Software Systems
Modularization and abstraction are the keys to practical verification and analysis of large and complex systems. We present in an incremental methodology for the automatic analysi...
Hassen Saïdi
IJCV
2000
164views more  IJCV 2000»
14 years 9 months ago
Probabilistic Modeling and Recognition of 3-D Objects
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
Joachim Hornegger, Heinrich Niemann