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» Asynchronous Distributed Learning of Topic Models
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NIPS
2008
11 years 2 months ago
Asynchronous Distributed Learning of Topic Models
Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
Arthur Asuncion, Padhraic Smyth, Max Welling
ACL
2010
10 years 11 months ago
PCFGs, Topic Models, Adaptor Grammars and Learning Topical Collocations and the Structure of Proper Names
This paper establishes a connection between two apparently very different kinds of probabilistic models. Latent Dirichlet Allocation (LDA) models are used as "topic models&qu...
Mark Johnson
WSDM
2009
ACM
136views Data Mining» more  WSDM 2009»
11 years 8 months ago
Mining common topics from multiple asynchronous text streams
Text streams are becoming more and more ubiquitous, in the forms of news feeds, weblog archives and so on, which result in a large volume of data. An effective way to explore the...
Xiang Wang 0002, Kai Zhang, Xiaoming Jin, Dou Shen
KDD
2006
ACM
177views Data Mining» more  KDD 2006»
12 years 1 months ago
Topics over time: a non-Markov continuous-time model of topical trends
This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work t...
Xuerui Wang, Andrew McCallum
AAAI
2010
11 years 2 months ago
A Two-Dimensional Topic-Aspect Model for Discovering Multi-Faceted Topics
This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristi...
Michael Paul, Roxana Girju
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