Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC [PDF]
arXiv, 2017 It is challenging to develop stochastic gradient based scalable inference for deep discrete latent variable models (LVMs), due to the difficulties in not only computing the gradients, but also adapting the step sizes to different latent factors and hidden layers.
arxiv
Discovering Style Trends through Deep Visually Aware Latent Item Embeddings [PDF]
arXiv, 2018 In this paper, we explore Latent Dirichlet Allocation (LDA) and Polylingual Latent Dirichlet Allocation (PolyLDA), as a means to discover trending styles in Overstock from deep visual semantic features transferred from a pretrained convolutional neural network and text-based item attributes.
arxiv
Dirichlet-vMF Mixture Model [PDF]
arXiv, 2017 This document is about the multi-document Von-Mises-Fisher mixture model with a Dirichlet prior, referred to as VMFMix. VMFMix is analogous to Latent Dirichlet Allocation (LDA) in that they can capture the co-occurrence patterns acorss multiple documents.
arxiv
Covid-19 Tweets Sentiment Analysis with Latent Dirichlet Allocation Topic Modeling
The Owl, 2022 Analysis of Covid-19 vaccine tweets has been an extensive focus in understanding user trends throughout the pandemic. This project concentrated on the development of a Latent Dirichlet Allocation (LDA) model along with sentiment analysis to better ...
Akhil Shiju
doaj
Extending Information Retrieval Methods to Personalized Genomic-Based Studies of Disease
Cancer Informatics, 2014 Genomic-based studies of disease now involve diverse types of data collected on large groups of patients. A major challenge facing statistical scientists is how best to combine the data, extract important features, and comprehensively characterize the ...
Shuyun Ye +2 more
doaj +1 more source
Latent Dirichlet Allocation in Generative Adversarial Networks [PDF]
arXiv, 2018 We study the problem of multimodal generative modelling of images based on generative adversarial networks (GANs). Despite the success of existing methods, they often ignore the underlying structure of vision data or its multimodal generation characteristics.
arxiv
Latent Dirichlet Allocation with topic-in-set knowledge [PDF]
, 2009 David Andrzejewski, Xiaojin Zhu
openalex +1 more source
Using Latent Dirichlet Allocation for automatic categorization of software [PDF]
, 2009 Kai Tian +2 more
openalex +1 more source
Feature extraction using Latent Dirichlet Allocation and Neural Networks: A case study on movie synopses [PDF]
arXiv, 2016 Feature extraction has gained increasing attention in the field of machine learning, as in order to detect patterns, extract information, or predict future observations from big data, the urge of informative features is crucial. The process of extracting features is highly linked to dimensionality reduction as it implies the transformation of the data ...
arxiv
Gaussian hierarchical latent Dirichlet allocation: Bringing polysemy back. [PDF]
PLoS One, 2023 Yoshida T, Hisano R, Ohnishi T.
europepmc +1 more source