Computer Science - Machine Learning

Combating Fake News: A Survey on Identification and Mitigation Techniques
The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of …
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Recurrent Neural Networks for Multivariate Time Series with Missing Values
Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety …
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Deep Generative Dual Memory Network for Continual Learning
Despite advances in deep learning, neural networks can only learn multiple tasks when trained on them jointly. When tasks arrive …
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Detecting Statistical Interactions from Neural Network Weights
Interpreting neural networks is a crucial and challenging task in machine learning. In this paper, we develop a novel framework for …
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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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CSI: A Hybrid Deep Model for Fake News Detection
The topic of fake news has drawn attention both from the public and the academic communities. Such misinformation has the potential of …
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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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