Mixed-Variate Restricted Boltzmann Machines

08/06/2014
by   Truyen Tran, et al.
0

Modern datasets are becoming heterogeneous. To this end, we present in this paper Mixed-Variate Restricted Boltzmann Machines for simultaneously modelling variables of multiple types and modalities, including binary and continuous responses, categorical options, multicategorical choices, ordinal assessment and category-ranked preferences. Dependency among variables is modeled using latent binary variables, each of which can be interpreted as a particular hidden aspect of the data. The proposed model, similar to the standard RBMs, allows fast evaluation of the posterior for the latent variables. Hence, it is naturally suitable for many common tasks including, but not limited to, (a) as a pre-processing step to convert complex input data into a more convenient vectorial representation through the latent posteriors, thereby offering a dimensionality reduction capacity, (b) as a classifier supporting binary, multiclass, multilabel, and label-ranking outputs, or a regression tool for continuous outputs and (c) as a data completion tool for multimodal and heterogeneous data. We evaluate the proposed model on a large-scale dataset using the world opinion survey results on three tasks: feature extraction and visualization, data completion and prediction.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/01/2014

Thurstonian Boltzmann Machines: Learning from Multiple Inequalities

We introduce Thurstonian Boltzmann Machines (TBM), a unified architectur...
research
07/31/2014

Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis

Ordinal data is omnipresent in almost all multiuser-generated feedback -...
research
05/25/2018

Learning Restricted Boltzmann Machines via Influence Maximization

Graphical models are a rich language for describing high-dimensional dis...
research
07/26/2017

General Latent Feature Modeling for Data Exploration Tasks

This paper introduces a general Bayesian non- parametric latent feature ...
research
03/18/2015

Shared latent subspace modelling within Gaussian-Binary Restricted Boltzmann Machines for NIST i-Vector Challenge 2014

This paper presents a novel approach to speaker subspace modelling based...
research
08/18/2017

Statistical Latent Space Approach for Mixed Data Modelling and Applications

The analysis of mixed data has been raising challenges in statistics and...
research
12/31/2017

Restricted Boltzmann Machines for Robust and Fast Latent Truth Discovery

We address the problem of latent truth discovery, LTD for short, where t...

Please sign up or login with your details

Forgot password? Click here to reset