A study on dual topic models and bayesian topic model inference
Topic models have been shown to be a powerful tool for organizing large collections of unstructured data, including text, images and location data. The essence of the topic model is to discover hidden clusters that summarize the relationship between two discrete random variables, such as documents a...
Saved in:
Main Author: | Rugeles, Daniel |
---|---|
Other Authors: | Gao CONG |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/145117 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Graphical models and variational Bayesian inference for financial networks
by: Xin, Luyin
Published: (2019) -
Differentiable generative models for trajectory data analytics
by: Li, Xiucheng
Published: (2020) -
Latent representation models for mining geo-spatial data
by: Liu, Yiding
Published: (2020) -
Pairwise copula cyclic graphical model for spatial extremes modeling
by: Zhu, Junting
Published: (2014) -
Inferensi Bayesian Pada Model Linier Regresi
by: Inna Kuswandari, -
Published: (1995)