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» Nonparametric Background Generation
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102
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MCS
2008
Springer
15 years 3 months ago
Detecting multiple mean breaks at unknown points in official time series
In this paper, we propose a computationally effective approach to detect multiple structural breaks in the mean occurring at unknown dates. We present a non-parametric approach th...
Carmela Cappelli, Richard N. Penny, William S. Rea...
118
Voted
JMLR
2010
92views more  JMLR 2010»
14 years 10 months ago
Posterior distributions are computable from predictive distributions
As we devise more complicated prior distributions, will inference algorithms keep up? We highlight a negative result in computable probability theory by Ackerman, Freer, and Roy (...
Cameron E. Freer, Daniel M. Roy
144
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Infinite-state spectrum model for music signal analysis
This paper presents a nonparametric Bayesian extension of nonnegative matrix factorization (NMF) for music signal analysis. Instrument sounds often exhibit non-stationary spectral...
Masahiro Nakano, Jonathan Le Roux, Hirokazu Kameok...
127
Voted
BMCBI
2004
161views more  BMCBI 2004»
15 years 3 months ago
Three-parameter lognormal distribution ubiquitously found in cDNA microarray data and its application to parametric data treatme
Background: To cancel experimental variations, microarray data must be normalized prior to analysis. Where an appropriate model for statistical data distribution is available, a p...
Tomokazu Konishi
179
Voted
CVPR
2008
IEEE
15 years 3 months ago
Tracking distributions with an overlap prior
Recent studies have shown that embedding similarity/dissimilarity measures between distributions in the variational level set framework can lead to effective object segmentation/t...
Ismail Ben Ayed, Shuo Li, Ian G. Ross