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UAI
2001
14 years 17 days ago
Improved learning of Bayesian networks
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Baye...
Tomás Kocka, Robert Castelo
UAI
2003
14 years 16 days ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
CORR
2010
Springer
142views Education» more  CORR 2010»
13 years 11 months ago
The Accuracy of Tree-based Counting in Dynamic Networks
Tree-based protocols are ubiquitous in distributed systems. They are flexible, they perform generally well, and, in static conditions, their analysis is mostly simple. Under churn...
Supriya Krishnamurthy, John Ardelius, Erik Aurell,...
TPDS
2008
96views more  TPDS 2008»
13 years 11 months ago
Stochastic Graph Processes for Performance Evaluation of Content Delivery Applications in Overlay Networks
This paper proposes a new methodology to model the distribution of finite size content to a group of users connected through an overlay network. Our methodology describes the distr...
Damiano Carra, Renato Lo Cigno, Ernst W. Biersack
GLOBECOM
2010
IEEE
13 years 9 months ago
Cooperation Stimulation in Cognitive Networks Using Indirect Reciprocity Game Modelling
In cognitive networks, since nodes generally belong to different authorities and pursue different goals, they will not cooperate with others unless cooperation can improve their ow...
Yan Chen, K. J. Ray Liu