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ICML
2008
IEEE
15 years 10 months ago
Laplace maximum margin Markov networks
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
Jun Zhu, Eric P. Xing, Bo Zhang
INFOCOM
2009
IEEE
15 years 4 months ago
Event Recognition in Sensor Networks by Means of Grammatical Inference
Abstract—Modern military and civilian surveillance applications should provide end users with the high level representation of events observed by sensors rather than with the raw...
Sahin Cem Geyik, Boleslaw K. Szymanski
CISS
2007
IEEE
15 years 3 months ago
Collector Receiver Design for Data Collection and Localization in Sensor-driven Networks
— We consider a sensor network in which the sensors communicate at will when they have something to report, without prior coordination with other sensors or with data collection ...
Bharath Ananthasubramaniam, Upamanyu Madhow
BMCBI
2008
145views more  BMCBI 2008»
14 years 9 months ago
Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis
Background: The combination of gene expression profiling with linkage analysis has become a powerful paradigm for mapping gene expression quantitative trait loci (eQTL). To date, ...
Shameek Biswas, John D. Storey, Joshua M. Akey
69
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AAAI
2004
14 years 11 months ago
Identifying Linear Causal Effects
This paper concerns the assessment of linear cause-effect relationships from a combination of observational data and qualitative causal structures. The paper shows how techniques ...
Jin Tian