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» A New Discriminative Kernel From Probabilistic Models
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ICDM
2007
IEEE
184views Data Mining» more  ICDM 2007»
15 years 4 months ago
Bayesian Folding-In with Dirichlet Kernels for PLSI
Probabilistic latent semantic indexing (PLSI) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation...
Alexander Hinneburg, Hans-Henning Gabriel, Andr&eg...
ISNN
2004
Springer
15 years 3 months ago
Realtime Monitoring of Vascular Conditions Using a Probabilistic Neural Network
Abstract. This paper proposes a new method to discriminate the vascular conditions from biological signals by using a probabilistic neural network, and develops the diagnosis suppo...
Akira Sakane, Toshio Tsuji, Yoshiyuki Tanaka, Kenj...
82
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ECCV
2000
Springer
15 years 11 months ago
A Probabilistic Background Model for Tracking
A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. Th...
Jens Rittscher, Jien Kato, Sébastien Joga, ...
68
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NIPS
2004
14 years 11 months ago
Outlier Detection with One-class Kernel Fisher Discriminants
The problem of detecting "atypical objects" or "outliers" is one of the classical topics in (robust) statistics. Recently, it has been proposed to address this...
Volker Roth
JMLR
2006
136views more  JMLR 2006»
14 years 9 months ago
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
Tonatiuh Peña Centeno, Neil D. Lawrence