7.1k citations · 7.1k across the 11 of their papers we have counts for
5 papers · 1 filter
Learning Sparse Deep Feedforward Networks via Tree Skeleton Expansion
Zhourong Chen, Xiaopeng Li, Nevin L. Zhang
Despite the popularity of deep learning, structure learning for deep models remains a relatively under-explored area. In contrast, structure learning has been studied extensively f…
Building Sparse Deep Feedforward Networks using Tree Receptive Fields
Xiaopeng Li, Zhourong Chen, Nevin L. Zhang
Sparse connectivity is an important factor behind the success of convolutional neural networks and recurrent neural networks. In this paper, we consider the problem of learning spa…
Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering
Xiaopeng Li, Zhourong Chen, Leonard K. M. Poon +1
We investigate a variant of variational autoencoders where there is a superstructure of discrete latent variables on top of the latent features. In general, our superstructure is a…
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…
Progressive EM for Latent Tree Models and Hierarchical Topic Detection
Peixian Chen, Nevin L. Zhang, Leonard K. M. Poon +1
Hierarchical latent tree analysis (HLTA) is recently proposed as a new method for topic detection. It differs fundamentally from the LDA-based methods in terms of topic definition,…