7 Result(s)
within
Simon Luo
Computer Science
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Article
Efficient EM-variational inference for nonparametric Hawkes process
The classic Hawkes process assumes the baseline intensity to be constant and the triggering kernel to be a parametric function. Differently, we present a generalization of the parametric Hawkes process by usin...
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Article
Multi-task learning by hierarchical Dirichlet mixture model for sparse failure prediction
Sparsity and noisy labels occur inherently in real-world data. Previously, strong assumptions were made by domain experts to use their experience and expertise to select parameters for their models. Similar ap...
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Article
Effects of personality traits on user trust in human–machine collaborations
Data analytics-driven solutions are widely used in various intelligent systems, where humans and machines make decisions collaboratively based on predictions. Human factors such as personality and trust have s...
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Chapter and Conference Paper
Semi-supervised Learning Approach to Generate Neuroimaging Modalities with Adversarial Training
Magnetic Resonance Imaging (MRI) of the brain can come in the form of different modalities such as T1-weighted and Fluid Attenuated Inversion Recovery (FLAIR) which has been used to investigate a wide range of...
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Chapter and Conference Paper
Multitask Learning for Sparse Failure Prediction
Sparsity is a problem which occurs inherently in many real-world datasets. Sparsity induces an imbalance in data, which has an adverse effect on machine learning and hence reducing the predictability. Previous...
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Chapter and Conference Paper
Exploring Latent Structure Similarity for Bayesian Nonparameteric Model with Mixture of NHPP Sequence
Temporal point process data has been widely observed in many applications including finance, health, and infrastructures, so that it has become an important topic in data analytics domain. Generally, a point p...
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Chapter and Conference Paper
Effects of Uncertainty and Cognitive Load on User Trust in Predictive Decision Making
Rapid increase of data in different fields has been resulting in wide applications of Machine Learning (ML) based intelligent systems in predictive decision making scenarios. Unfortunately, these systems appe...
