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» Theory and Use of the EM Algorithm
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ICML
2004
IEEE
16 years 5 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
ICML
2005
IEEE
16 years 5 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
KDD
2008
ACM
244views Data Mining» more  KDD 2008»
16 years 5 months ago
Probabilistic latent semantic visualization: topic model for visualizing documents
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
ICC
2009
IEEE
107views Communications» more  ICC 2009»
15 years 11 months ago
EM-Based Maximum-Likelihood Sequence Detection for MIMO Optical Wireless Systems
—A major performance-limiting factor in terrestrial optical wireless (OW) systems is turbulence-induced fading. Exploiting the additional degrees of freedom in the spatial dimens...
Nestor D. Chatzidiamantis, Murat Uysal, Theodoros ...
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SSPR
2004
Springer
15 years 10 months ago
Clustering with Soft and Group Constraints
Several clustering algorithms equipped with pairwise hard constraints between data points are known to improve the accuracy of clustering solutions. We develop a new clustering alg...
Martin H. C. Law, Alexander P. Topchy, Anil K. Jai...