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Our third and final session will have two presentations “Prediction of hospital demand from the COVID-19 death curve: IHME Model” and “Molecular epidemiology of SARS-Cov-2: what…
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Title: Is Deep Learning a Black Box Statistically? Abstract: Deep learning has benefited almost every aspect of modern big data applications. Yet its statistical properties still largely remain…
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Selective Inference is the problem of testing hypotheses that are chosen or suggested by the
data. Inference after variable selection in high-dimensional linear regression is a common
example of…
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The information revolution is spawning systems that require very frequent decisions and provide high volumes of data concerning past outcomes. Fueling the design of algorithms used in such systems is…
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Continuous optimization is a key component of modern data analysis. Recently, the demands
of extremely large-scale applications have shifted the focus from high cost, high accuracy
methods to low…
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Tuesday, March 25, 2014 at 4:15pm
Frank H. T. Rhodes Hall, 253
ORIE Colloquium: Rob Freund (MIT) - A First-Order View of Some Boosting Methods: Computational Guarantees and Connections to…
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Thursday, February 6, 2014 at 4:15pm
Frank H. T. Rhodes Hall, 253
ORIE Colloquium: Po-Ling Loh (Cal-Berkeley) - Nonconvex Methods for High-Dimensional Regression with Noisy and Missing Data
Noisy…
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Many operational problems in data-rich environments can be characterized by three primitives: data on uncertain quantities of interest such as simultaneous demands, concurrent auxiliary data such as…
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Computing reliable solutions to inverse problems is important in many applications such as biomedical imaging, computer graphics, and security. Regularization by incorporating prior knowledge is…
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ORIE/Statistics Colloquium: Sahand Negahban (MIT) - Structured Estimation in High-Dimensions
Wednesday, February 20, 2013 at 4:15pm
Frank H. T. Rhodes Hall, 253
Modern techniques in data…
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In many markets, it is common for headquarters to create a price list while local salespeople have discretion to negotiate prices for individual deals. How much (if any) pricing discretion to grant…
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Standard approaches to solving stochastic dynamic programs suffer from the curse of dimensionality. Taking advantage of structural properties such as convexity can help reduce the effect of dimension…
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