Search for tag: "regression analysis"
Mathmatical Modeling Infectious Disease IIIOur 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…
From Dave Frank
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ORIE Colloquium, 2018-10-29 - Jinchi Lv: Is Deep Learning a Black Box Statistically?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…
From E. Cornelius
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ORIE Colloquium on 1/29/2015 - Jason Lee: Selective Inference via the Condition on Selection Framework: Applications to Inference After Variable SelectionSelective 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…
From E. Cornelius
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ORIE Colloquium, 2015-01-16 - Daniel Russo: Learning to OptimizeThe 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…
From E. Cornelius
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ORIE Colloquium, 2015-01-26 - Damek Davis: The Design and Analysis of Large-scale Operator-splitting SchemesContinuous 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…
From E. Cornelius
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ORIE Colloquium on 3/25/2014 - Rob Freund: A First-Order View of Some Boosting Methods: Computational Guarantees and Connections to RegularizationTuesday, 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…
From E. Cornelius
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ORIE Colloquium on 2/6/2014 - Po-Ling Loh (Cal-Berkeley): Nonconvex Methods for High-Dimensional Regression with Noisy and Missing DataThursday, 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…
From E. Cornelius
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ORIE Colloquium, 2014-12-19 - Nathan Kallus: From Predictive to Prescriptive AnalyticsMany 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…
From E. Cornelius
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CAM Colloquium September 19, 2014 - Julianne Chung: Designing Optimal Spectral Filters and Low-Rank Matrices for Inverse ProblemsComputing reliable solutions to inverse problems is important in many applications such as biomedical imaging, computer graphics, and security. Regularization by incorporating prior knowledge is…
From E. Cornelius
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ORIE Colloquium, 2013-02-20 - Sahand Negahban: Structured Estimation in High-DimensionsORIE/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…
From E. Cornelius
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ORIE Colloquium on 9/17/2013 - Serdar Simsek: Does Field Price Discretion Improve Profits? Evidence from Auto LendingIn 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…
From E. Cornelius
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ORIE Colloquium on 11/29/2011 - John Birge: Monte Carlo and Bayesian Methods for Stochastic Dynamic ProgramsStandard 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…
From E. Cornelius
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