stat.ML

The Graph-Based Behavior-Aware Recommendation for Interactive News
Interactive news recommendation has been launched and attracted much attention recently. In this scenario, user’s behavior evolves from …
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High-dimensional Index Volatility Models via Stein's Identity
We study the estimation of the parametric components of single and multiple index volatility models. Using the first- and second-order …
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AEGCN: An Autoencoder-Constrained Graph Convolutional Network
We propose a novel neural network architecture, called autoencoder-constrained graph convolutional network, to solve node …
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Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity
Differential graphical models are designed to represent the difference between the conditional dependence structures of two groups, and …
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Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Graph representation learning is a ubiquitous task in machine learning where the goal is to embed each vertex into a low-dimensional …
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High-dimensional Varying Index Coefficient Models via Stein's Identity
We study the parameter estimation problem for a varying index coefficient model in high dimensions. Unlike the most existing works that …
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