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» Exponentiable morphisms of domains
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NIPS
2008
13 years 9 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
OPODIS
2003
13 years 9 months ago
Detecting Temporal Logic Predicates in Distributed Programs Using Computation Slicing
Detecting whether a finite execution trace (or a computation) of a distributed program satisfies a given predicate, called predicate detection, is a fundamental problem in distr...
Alper Sen, Vijay K. Garg
UAI
2000
13 years 8 months ago
Being Bayesian about Network Structure
In many domains, we are interested in analyzing the structure of the underlying distribution, e.g., whether one variable is a direct parent of the other. Bayesian model selection a...
Nir Friedman, Daphne Koller
ATAL
2010
Springer
13 years 8 months ago
Decision making with dynamically arriving information
Decision making is the ability to decide on the best alternative among a set of candidates based on their value. In many real-world domains the value depends on events that occur ...
Meir Kalech, Avi Pfeffer
ECAI
2010
Springer
13 years 8 months ago
Metric Propositional Neighborhood Logics: Expressiveness, Decidability, and Undecidability
Abstract. Interval temporal logics formalize reasoning about interval structures over (usually) linearly ordered domains, where time intervals are the primitive ontological entitie...
Davide Bresolin, Dario Della Monica, Valentin Gora...