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» The Information Bottleneck EM Algorithm
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EMNLP
2010
13 years 5 months ago
Latent-Descriptor Clustering for Unsupervised POS Induction
We present a novel approach to distributionalonly, fully unsupervised, POS tagging, based on an adaptation of the EM algorithm for the estimation of a Gaussian mixture. In this ap...
Michael Lamar, Yariv Maron, Elie Bienenstock
NIPS
2004
13 years 9 months ago
On Semi-Supervised Classification
A graph-based prior is proposed for parametric semi-supervised classification. The prior utilizes both labelled and unlabelled data; it also integrates features from multiple view...
Balaji Krishnapuram, David Williams, Ya Xue, Alexa...
ICDE
2006
IEEE
144views Database» more  ICDE 2006»
14 years 8 months ago
Super-Scalar RAM-CPU Cache Compression
High-performance data-intensive query processing tasks like OLAP, data mining or scientific data analysis can be severely I/O bound, even when high-end RAID storage systems are us...
Marcin Zukowski, Niels Nes, Peter A. Boncz, S&aacu...
PCI
2005
Springer
14 years 1 months ago
Gossip-Based Greedy Gaussian Mixture Learning
Abstract. It has been recently demonstrated that the classical EM algorithm for learning Gaussian mixture models can be successfully implemented in a decentralized manner by resort...
Nikos A. Vlassis, Yiannis Sfakianakis, Wojtek Kowa...
IPM
2008
102views more  IPM 2008»
13 years 7 months ago
Fast exact maximum likelihood estimation for mixture of language model
Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language mo...
Yi Zhang 0001, Wei Xu