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Biostatistics Seminar: Reframing Proportional-Hazards Modeling for Large Time-to-Event Datasets with Applications to Deep Learning
We are welcoming Dr. Simon, who will talk about “Reframing proportional-hazards modeling for large time-to-event datasets with applications to deep learning.” Dr. Simon works on machine learning (including penalized regression and classification), efficient algorithms in high dimensional spaces, shrinkage estimation and clinical trial design. The techniques he develops are directed at problems in biology and medical science (though they are often more widely applicable).
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