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ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 8 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
TACAS
2000
Springer
138views Algorithms» more  TACAS 2000»
14 years 1 months ago
Symbolic Model Checking of Probabilistic Processes Using MTBDDs and the Kronecker Representation
This paper reports on experimental results with symbolic model checking of probabilistic processes based on Multi-Terminal Binary Decision Diagrams (MTBDDs). We consider concurrent...
Luca de Alfaro, Marta Z. Kwiatkowska, Gethin Norma...
FOIS
2006
13 years 11 months ago
PR-OWL: A Framework for Probabilistic Ontologies
Abstract. Across a wide range of domains, there is an urgent need for a wellfounded approach to incorporating uncertain and incomplete knowledge into formal domain ontologies. Alth...
Paulo Cesar G. da Costa, Kathryn B. Laskey
SCL
2008
76views more  SCL 2008»
13 years 10 months ago
Probabilistic output admissible set for systems with time-varying uncertainties
This paper considers time-varying uncertain constrained systems, and develops a method for computing a probabilistic output admissible (POA) set. This set consists of the initial ...
Takeshi Hatanaka, Kiyotsugu Takaba
NIPS
2004
13 years 11 months ago
Common-Frame Model for Object Recognition
A generative probabilistic model for objects in images is presented. An object consists of a constellation of features. Feature appearance and pose are modeled probabilistically. ...
Pierre Moreels, Pietro Perona