Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation

by   Bei Chen, et al.

We present a discriminative nonparametric latent feature relational model (LFRM) for link prediction to automatically infer the dimensionality of latent features. Under the generic RegBayes (regularized Bayesian inference) framework, we handily incorporate the prediction loss with probabilistic inference of a Bayesian model; set distinct regularization parameters for different types of links to handle the imbalance issue in real networks; and unify the analysis of both the smooth logistic log-loss and the piecewise linear hinge loss. For the nonconjugate posterior inference, we present a simple Gibbs sampler via data augmentation, without making restricting assumptions as done in variational methods. We further develop an approximate sampler using stochastic gradient Langevin dynamics to handle large networks with hundreds of thousands of entities and millions of links, orders of magnitude larger than what existing LFRM models can process. Extensive studies on various real networks show promising performance.


page 1

page 2

page 3

page 4


Max-Margin Nonparametric Latent Feature Models for Link Prediction

Link prediction is a fundamental task in statistical network analysis. R...

Discriminative Relational Topic Models

Many scientific and engineering fields involve analyzing network data. F...

Nonparametric Bayes dynamic modeling of relational data

Symmetric binary matrices representing relations among entities are comm...

Scalable Deep Generative Relational Models with High-Order Node Dependence

We propose a probabilistic framework for modelling and exploring the lat...

The Nonparametric Metadata Dependent Relational Model

We introduce the nonparametric metadata dependent relational (NMDR) mode...

Bayesian nonparametric comorbidity analysis of psychiatric disorders

The analysis of comorbidity is an open and complex research field in the...

Bayesian nonparametric models for ranked data

We develop a Bayesian nonparametric extension of the popular Plackett-Lu...

Please sign up or login with your details

Forgot password? Click here to reset