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Estimating Likelihoods for Topic Models

Date

Authors

Buntine, Wray

Publisher

Springer

Abstract

Topic models are a discrete analogue to principle component analysis and independent component analysis that model topic at the word level within a document. They have many variants such as NMF, PLSI and LDA, and are used in many fields such as genetics,

Keywords

Keywords: Model comparison; Principle component analysis; Recommender systems; Topic model; Word level; Image analysis; Models; Robot learning; Independent component analysis

URI

http://hdl.handle.net/1885/19958

Collections

ANU Research Publications

Source

Proceedings of ACML 2009

Type

Conference paper

DOI

10.1007/978-3-642-05224-8_6

Restricted until

2037-12-31

Downloads

File

Description

01_Buntine_Estimating_Likelihoods_for_2009.pdf (248.77 KB)

02_Buntine_Estimating_Likelihoods_for_2009.pdf (138.54 KB)

03_Buntine_Estimating_Likelihoods_for_2009.pdf (273.97 KB)