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JMLR
2010
149views more  JMLR 2010»
14 years 4 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
IJAR
2010
113views more  IJAR 2010»
14 years 8 months ago
A geometric view on learning Bayesian network structures
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
Milan Studený, Jirí Vomlel, Raymond ...
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
14 years 11 months ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
TNN
1998
123views more  TNN 1998»
14 years 9 months ago
A general framework for adaptive processing of data structures
—A structured organization of information is typically required by symbolic processing. On the other hand, most connectionist models assume that data are organized according to r...
Paolo Frasconi, Marco Gori, Alessandro Sperduti
ICNSC
2007
IEEE
15 years 4 months ago
Analysis of a Simple Feedback Scheme for Error Correction over a Lossy Network
Abstract— In time varying packet-switched networks, delivering data with high reliability using a limited amount of network resources is highly desirable. To capture the trade-of...
Oscar Flardh, Carlo Fischione, Karl Henrik Johanss...