Abstract: High-dimensional time series from changing environments are collected in many applications and are prevalent in biology and medicine. Ignoring these changes, or assuming stationarity,…
Abstract: In a world that celebrates exceptionalism, the contributions of everyday professionals often go unnoticed. Funding favors "exceptional" work, but real progress depends on the many,…
Abstract: A major challenge in the age of Big Data is the integration of disparate data types into a single data analysis. That is tackled…
Abstract: The growing prevalence of digital health technologies has led to the generation of complex multi-modal data, such as physical activity measurements simultaneously collected from…
Abstract: Machine Learning ingests vast amounts of training data. That data may contain sensitive information and there is a risk that this information is revealed…
Abstract: Covariate-adjusted response adaptive (CARA) designs have gained widespread adoption for their clear benefits in enhancing experimental efficiency and participant welfare. These designs dynamically adjust…
Due to unforeseen circumstances, this talk has been canceled. Abstract: This study introduces Variational Automatic Relevance Determination (VARD), a novel approach for fitting sparse additive…
Abstract: The use of Artificial Intelligence (AI), or more generally data-driven algorithms, has become ubiquitous in today's society. Yet, in many cases and especially when…
Abstract: Motivated by Alzheimer’s disease (AD) research need to predict risk of cognitive decline dynamically based on various biomarkers and risk factors in the presence…
Abstract: Quantum computation and quantum information are of great current interest across various fields, including computer science, mathematics and statistics, physical sciences and engineering. As…
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