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» Advances in Mixture Models
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KDD
2005
ACM
112views Data Mining» more  KDD 2005»
16 years 5 months ago
Model-based overlapping clustering
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh,...
107
Voted
CORR
2006
Springer
101views Education» more  CORR 2006»
15 years 4 months ago
MDL Convergence Speed for Bernoulli Sequences
The Minimum Description Length principle for online sequence estimation/prediction in a proper learning setup is studied. If the underlying model class is discrete, then the total...
Jan Poland, Marcus Hutter
119
Voted
ICMCS
2007
IEEE
132views Multimedia» more  ICMCS 2007»
15 years 11 months ago
Two-Layer Generative Models for Sport Video Mining
We present a two-layer generative model for sport video mining that is composed of a two-layer observation model. The first layer is the Gaussian mixture model (GMM) using framew...
Yi Ding, Guoliang Fan, W. Bryan
INTERSPEECH
2010
14 years 11 months ago
Canonical state models for automatic speech recognition
Current speech recognition systems are often based on HMMs with state-clustered Gaussian Mixture Models (GMMs) to represent the context dependent output distributions. Though high...
Mark J. F. Gales, Kai Yu
FGR
2000
IEEE
123views Biometrics» more  FGR 2000»
15 years 9 months ago
A Fast and Accurate Face Detector for Indexation of Face Images
Detecting faces in images with complex backgrounds is a difficult task. Our approach, which obtains state of the art results, is based on a generative neural network model: the C...
Raphaël Feraud, Olivier Bernier, Jean-Emmanue...