Statistics - Machine Learning

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
Spatiotemporal forecasting has various applications in neuroscience, climate and transportation domain. Traffic forecasting is one …
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Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets
Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, …
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Tensor Regression Meets Gaussian Processes
Low-rank tensor regression, a new model class that learns high-order correlation from data, has recently received considerable …
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Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records
The rapid growth of Electronic Health Records (EHRs), as well as the accompanied opportunities in Data-Driven Healthcare (DDH), has …
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On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps
Positive-definite kernel functions are fundamental elements of kernel methods and Gaussian processes. A well-known construction of such …
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Model Selection for Topic Models via Spectral Decomposition
Topic models have achieved significant successes in analyzing large-scale text corpus. In practical applications, we are always …
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Spectral Sparsification of Random-Walk Matrix Polynomials
We consider a fundamental algorithmic question in spectral graph theory: Compute a spectral sparsifier of random-walk matrix-polynomial …
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Scalable Parallel Factorizations of SDD Matrices and Efficient Sampling for Gaussian Graphical Models
Motivated by a sampling problem basic to computational statistical inference, we develop a nearly optimal algorithm for a fundamental …
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Transfer Topic Modeling with Ease and Scalability
The increasing volume of short texts generated on social media sites, such as Twitter or Facebook, creates a great demand for effective …
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