23 citations · 62 across the 6 of their papers we have counts for
10 papers
Peacock: Learning Long-Tail Topic Features for Industrial Applications
Yi Wang, Xuemin Zhao, Zhenlong Sun +7
Latent Dirichlet allocation (LDA) is a popular topic modeling technique in academia but less so in industry, especially in large-scale applications involving search engine and onli…
Towards Big Topic Modeling
Jian-Feng Yan, Jia Zeng, Zhi-Qiang Liu +1
To solve the big topic modeling problem, we need to reduce both time and space complexities of batch latent Dirichlet allocation (LDA) algorithms. Although parallel LDA algorithms…
Fast Online EM for Big Topic Modeling
Jia Zeng, Zhi-Qiang Liu, Xiao-Qin Cao
The expectation-maximization (EM) algorithm can compute the maximum-likelihood (ML) or maximum a posterior (MAP) point estimate of the mixture models or latent variable models such…
Communication-Efficient Parallel Belief Propagation for Latent Dirichlet Allocation
Jian-feng Yan, Zhi-Qiang Liu, Yang Gao +1
This paper presents a novel communication-efficient parallel belief propagation (CE-PBP) algorithm for training latent Dirichlet allocation (LDA). Based on the synchronous belief p…
Memory-Efficient Topic Modeling
Jia Zeng, Zhi-Qiang Liu, Xiao-Qin Cao
As one of the simplest probabilistic topic modeling techniques, latent Dirichlet allocation (LDA) has found many important applications in text mining, computer vision and computat…
Residual Belief Propagation for Topic Modeling
Jia Zeng, Xiao-Qin Cao, Zhi-Qiang Liu
Fast convergence speed is a desired property for training latent Dirichlet allocation (LDA), especially in online and parallel topic modeling for massive data sets. This paper pres…