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NIPS
2007
13 years 10 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
CORR
2010
Springer
94views Education» more  CORR 2010»
13 years 8 months ago
Real-Time Multi-path Tracking of Probabilistic Available Bandwidth
Applications such as traffic engineering and network provisioning can greatly benefit from knowing, in real time, what is the largest input rate at which it is possible to transmit...
Frederic Thouin, Mark Coates, Michael Rabbat
PVLDB
2008
122views more  PVLDB 2008»
13 years 8 months ago
Exploiting shared correlations in probabilistic databases
There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources -from sensor data, experimental data, data fro...
Prithviraj Sen, Amol Deshpande, Lise Getoor
RSCTC
2000
Springer
126views Fuzzy Logic» more  RSCTC 2000»
14 years 8 days ago
Evolutionary Parsing for a Probabilistic Context Free Grammar
Abstract. Classic parsing methods are based on complete search techniques to find the different interpretations of a sentence. However, the size of the search space increases expon...
Lourdes Araujo
EDBT
2009
ACM
124views Database» more  EDBT 2009»
13 years 12 months ago
Processing probabilistic spatio-temporal range queries over moving objects with uncertainty
Range queries for querying the current and future positions of the moving objects have received growing interests in the research community. Existing methods, however, assume that...
Bruce S. E. Chung, Wang-Chien Lee, Arbee L. P. Che...