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Online Learning for Two Novel Latent Topic Models
Abstract : Latent topic models have proven to be an efficient tool for modeling multitopic count data. One of the most well-known models is the latent Dirichlet allocation (LDA). In this paper we propose two improvements for LDA using generalized Dirichlet and Beta-Liouville prior assumptions. Moreover, we apply an online learning approach for both introduced approaches. We choose a challenging application namely natural scene classification for comparison and evaluation purposes.
Cited literature [17 references]
https://hal.inria.fr/hal-01397223
Contributor : Hal Ifip <>
Submitted on : Tuesday, November 15, 2016 - 3:47:28 PM
Last modification on : Thursday, July 26, 2018 - 2:08:02 PM
Long-term archiving on: : Thursday, March 16, 2017 - 1:22:07 PM
Contributor : Hal Ifip <>
Submitted on : Tuesday, November 15, 2016 - 3:47:28 PM
Last modification on : Thursday, July 26, 2018 - 2:08:02 PM
Long-term archiving on: : Thursday, March 16, 2017 - 1:22:07 PM
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