3 papers
cs.CL2017
A Novel Document Generation Process for Topic Detection based on Hierarchical Latent Tree Models
Peixian Chen, Zhourong Chen, Nevin L. Zhang
We propose a novel document generation process based on hierarchical latent tree models (HLTMs) learned from data. An HLTM has a layer of observed word variables at the bottom and…
cs.LG2016
Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis
Zhourong Chen, Nevin L. Zhang, Dit-Yan Yeung +1
We are interested in exploring the possibility and benefits of structure learning for deep models. As the first step, this paper investigates the matter for Restricted Boltzmann Ma…
cs.CL2016
Latent Tree Models for Hierarchical Topic Detection
Peixian Chen, Nevin L. Zhang, Tengfei Liu +3
We present a novel method for hierarchical topic detection where topics are obtained by clustering documents in multiple ways. Specifically, we model document collections using a c…