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» Structure learning of Bayesian networks using constraints
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HICSS
2005
IEEE
160views Biometrics» more  HICSS 2005»
15 years 9 months ago
Using Content and Process Scaffolds to Support Collaborative Discourse in Asynchronous Learning Networks
Discourse, a form of collaborative learning [44], is one of the most widely used methods of teaching and learning in the online environment. Particularly in large courses, discour...
I. Wong-Bushby, Starr Roxanne Hiltz, Michael Biebe...
203
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WOWMOM
2005
ACM
240views Multimedia» more  WOWMOM 2005»
15 years 9 months ago
An Adaptive Routing Protocol for Ad Hoc Peer-to-Peer Networks
Ad hoc networks represent a key factor in the evolution of wireless communications. These networks typically consist of equal nodes that communicate without central control, inter...
Luca Gatani, Giuseppe Lo Re, Salvatore Gaglio
GECCO
2004
Springer
155views Optimization» more  GECCO 2004»
15 years 9 months ago
Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Shingo Mabu, Kotaro Hirasawa, Jinglu Hu
CP
2007
Springer
15 years 8 months ago
Efficient Computation of Minimal Point Algebra Constraints by Metagraph Closure
Abstract. Computing the minimal network (or minimal CSP) representation of a given set of constraints over the Point Algebra (PA) is a fundamental reasoning problem. In this paper ...
Alfonso Gerevini, Alessandro Saetti
IJCAI
2007
15 years 5 months ago
Recursive Random Fields
A formula in first-order logic can be viewed as a tree, with a logical connective at each node, and a knowledge base can be viewed as a tree whose root is a conjunction. Markov l...
Daniel Lowd, Pedro Domingos