17 citations · 17 across the 2 of their papers we have counts for
3 papers
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…