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» Bayesian Inference for PCFGs via Markov Chain Monte Carlo
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KDD
2004
ACM
170views Data Mining» more  KDD 2004»
13 years 11 months ago
Estimating the size of the telephone universe: a Bayesian Mark-recapture approach
Mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. In this article we adapt a finite mixture mark-recapture model i...
David Poole
ICPR
2008
IEEE
14 years 13 days ago
Object-of-interest extraction by integrating stochastic inference with learnt active shape sketch
This article presents a novel integrated approach to object of interest extraction, including learning to define target pattern and extracting by combining detection and segmenta...
Hongwei Li, Liang Lin, Tianfu Wu, Xiaobai Liu, Lan...
IPSN
2004
Springer
13 years 11 months ago
A probabilistic approach to inference with limited information in sensor networks
We present a methodology for a sensor network to answer queries with limited and stochastic information using probabilistic techniques. This capability is useful in that it allows...
Rahul Biswas, Sebastian Thrun, Leonidas J. Guibas
ICASSP
2011
IEEE
12 years 9 months ago
MCMC inference of the shape and variability of time-response signals
Signals in response to time-localized events of a common phenomenon tend to exhibit a common shape, but with variable time scale, amplitude, and delay across trials in many domain...
Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Ale...
ICASSP
2011
IEEE
12 years 9 months ago
Bayesian Compressive Sensing for clustered sparse signals
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
Lei Yu, Hong Sun, Jean-Pierre Barbot, Gang Zheng