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JMLR
2010
143views more  JMLR 2010»
13 years 2 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
KDD
2006
ACM
157views Data Mining» more  KDD 2006»
14 years 8 months ago
Using structure indices for efficient approximation of network properties
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...
Matthew J. Rattigan, Marc Maier, David Jensen
MOBICOM
2006
ACM
14 years 1 months ago
Fast and reliable estimation schemes in RFID systems
RFID tags are being used in many diverse applications in increasingly large numbers. These capabilities of these tags span from very dumb passive tags to smart active tags, with t...
Murali S. Kodialam, Thyaga Nandagopal
JMLR
2010
140views more  JMLR 2010»
13 years 2 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
KES
2010
Springer
13 years 6 months ago
Extracting a Keyword Network of Flood Disaster Measures
For rapid and effective recovery from a flood disaster, an anti-disaster headquarters must not only assess the extent of damage, but also possess overall knowledge of the possibl...
Motoki Miura, Mitsuhiro Tokuda, Daiki Kuwahara