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    » Hybrid Variational Gibbs Collapsed Inference in Topic Models
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    ICML
    2007
    IEEE
    197views Machine Learning» more  ICML 2007»
    A permutation-augmented sampler for DP mixture models
    14 years 9 months ago
    A permutation-augmented sampler for DP mixture models
    Download  www.machinelearning.org
    We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
    Percy Liang, Michael I. Jordan, Benjamin Taskar
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    EMNLP
    2010
    170views Natural Language Processing» more  EMNLP 2010»
    Staying Informed: Supervised and Semi-Supervised Multi-View Topical Analysis of Ideological Perspective
    13 years 6 months ago
    Staying Informed: Supervised and Semi-Supervised Multi-View Topical Analysis of Ideological Perspective
    Download  www.cs.cmu.edu
    With the proliferation of user-generated articles over the web, it becomes imperative to develop automated methods that are aware of the ideological-bias implicit in a document co...
    Amr Ahmed, Eric P. Xing
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    DSP
    2007
    137views Emerging Technology» more  DSP 2007»
    Variational and stochastic inference for Bayesian source separation
    13 years 8 months ago
    Variational and stochastic inference for Bayesian source separation
    Download  perso.telecom-paristech.fr
    We tackle the general linear instantaneous model (possibly underdetermined and noisy) where we model the source prior with a Student t distribution. The conjugate-exponential char...
    Ali Taylan Cemgil, Cédric Févotte, S...
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    ICML
    2009
    IEEE
    215views Machine Learning» more  ICML 2009»
    Incorporating domain knowledge into topic modeling via Dirichlet Forest priors
    14 years 9 months ago
    Incorporating domain knowledge into topic modeling via Dirichlet Forest priors
    Download  www.biostat.wisc.edu
    Users of topic modeling methods often have knowledge about the composition of words that should have high or low probability in various topics. We incorporate such domain knowledg...
    David Andrzejewski, Xiaojin Zhu, Mark Craven
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    KDD
    2009
    ACM
    191views Data Mining» more  KDD 2009»
    Efficient methods for topic model inference on streaming document collections
    14 years 9 months ago
    Efficient methods for topic model inference on streaming document collections
    Download  www.cs.umass.edu
    Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
    Limin Yao, David M. Mimno, Andrew McCallum
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