24 citations · 58 across the 8 of their papers we have counts for
9 papers
Two-Stage Holistic and Contrastive Explanation of Image Classification
Weiyan Xie, Xiao-Hui Li, Zhi Lin +3
The need to explain the output of a deep neural network classifier is now widely recognized. While previous methods typically explain a single class in the output, we advocate expl…
Learning the Structure of Auto-Encoding Recommenders
Farhan Khawar, Leonard Kin Man Poon, Nevin Lianwen Zhang
Autoencoder recommenders have recently shown state-of-the-art performance in the recommendation task due to their ability to model non-linear item relationships effectively. Howeve…
Handling Collocations in Hierarchical Latent Tree Analysis for Topic Modeling
Leonard K. M. Poon, Nevin L. Zhang, Haoran Xie +1
Topic modeling has been one of the most active research areas in machine learning in recent years. Hierarchical latent tree analysis (HLTA) has been recently proposed for hierarchi…
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…
Latent Tree Analysis
Nevin L. Zhang, Leonard K. M. Poon
Latent tree analysis seeks to model the correlations among a set of random variables using a tree of latent variables. It was proposed as an improvement to latent class analysis --…
Topic Browsing for Research Papers with Hierarchical Latent Tree Analysis
Leonard K. M. Poon, Nevin L. Zhang
Academic researchers often need to face with a large collection of research papers in the literature. This problem may be even worse for postgraduate students who are new to a fiel…
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…
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,…
A Model-Based Approach to Rounding in Spectral Clustering
Leonard K. M. Poon, April H. Liu, Tengfei Liu +1
In spectral clustering, one defines a similarity matrix for a collection of data points, transforms the matrix to get the Laplacian matrix, finds the eigenvectors of the Laplacian…