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» Decision Making Using Probabilistic Inference Methods
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DILS
2009
Springer
15 years 10 months ago
Integration of Full-Coverage Probabilistic Functional Networks with Relevance to Specific Biological Processes
Probabilistic functional integrated networks are powerful tools with which to draw inferences from high-throughput data. However, network analyses are generally not tailored to spe...
Katherine James, Anil Wipat, Jennifer Hallinan
IDA
2005
Springer
15 years 9 months ago
Combining Bayesian Networks with Higher-Order Data Representations
Abstract. This paper introduces Higher-Order Bayesian Networks, a probabilistic reasoning formalism which combines the efficient reasoning mechanisms of Bayesian Networks with the...
Elias Gyftodimos, Peter A. Flach
SAC
2006
ACM
15 years 10 months ago
Decoupling classes with inferred interfaces
Using small, context-specific interfaces in variable declarations serves the decoupling of classes and increases a program’s flexibility. To minimize its interface, a thorough a...
Friedrich Steimann, Philip Mayer, Andreas Meissner
AIPS
2007
15 years 6 months ago
Discovering Relational Domain Features for Probabilistic Planning
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
Jia-Hong Wu, Robert Givan
AAAI
2007
15 years 6 months ago
Recognizing Textual Entailment Using a Subsequence Kernel Method
We present a novel approach to recognizing Textual nt. Structural features are constructed from abstract tree descriptions, which are automatically extracted from syntactic depend...
Rui Wang 0005, Günter Neumann