Search for tag: "statistical models"

Milstein Invited Lecture - Keyon Vafa

Zoom Recording ID: 96610307248 UUID: Ulr/E83kRWGGHY19KZmk9A== Meeting Time: 2020-06-25T23:47:07Z

From  Tapan Parikh 56 plays

Mathmatical Modeling Infectious Disease III

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…

From  Dave Frank 47 plays

ORIE Colloquium, 3/18/2020 - Ashia Wilson

“Variational Perspectives on Machine Learning: Algorithms, Inference, and Fairness”Machine learning plays a key role in shaping the decisions made by a growing number of institutions.…

From  E. Cornelius 179 plays

Is Global Agriculture Growing more Resilient to Climate Shocks?

Ariel Ortiz-Bobea, Assistant Professor, College of Agriculture and Life Sciences, Charles H. Dyson School of Applied Economics and Management. June 17th, 2019.

From  Jennifer Wright 31 plays

CS2110-FA17-26 Session 26

2017-11-22 00:00:00+00

From  mjp337@cornell.edu 121 plays

ORIE 9000 Colloquium - Xiaodong Li: Low-rank recovery: from convex to nonconvex methods

Low-rank structures are common in modern data analysis, and they play essential roles in various applications. It is challenging to recover low-rank structures reliably and ef´Čüciently from corrupted…

From  E. Cornelius 0 plays

ORIE Colloquium on 2/18/2015 - Mariana Olvera-Cravioto: Queues in the Cloud: Generalizing the single server queue to massively parallel networks

Motivated by today’s cloud computing capabilities in large server farms, we present a queueing model where jobs are split into a number of pieces which are then randomly routed to…

From  E. Cornelius 4 plays

ORIE 9000 Colloquium - Madeleine Udell: Generalized Low Rank Models

Principal components analysis (PCA) is a well-known technique for approximating a data set represented by a matrix by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets…

From  E. Cornelius 6 plays

ORIE Colloquium on 1/29/2015 - Jason Lee: Selective Inference via the Condition on Selection Framework: Applications to Inference After Variable Selection

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…

From  E. Cornelius 6 plays

ORIE Colloquium, 2015-01-16 - Daniel Russo: Learning to Optimize

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…

From  E. Cornelius 155 plays

CAM Colloquium - Ioannis Papastathopoulos: High-dimensional inference for multivariate extremes

Natural hazards such as floods, heatwaves and windstorms can cause havoc for the people affected and typically result in huge financial losses. Drug-induced liver injury is a major public health and…

From  E. Cornelius 6 plays

CAM Colloquium - Adrian Lewis: Nonsmooth optimization: conditioning, convergence, and semi-algebraic models

Variational analysis has come of age. Long an elegant theoretical toolkit for variational mathematics and nonsmooth optimization, it now increasingly underpins the study of algorithms, and a rich…

From  E. Cornelius 64 plays

ORIE Colloquium on 3/25/2014 - Rob Freund: A First-Order View of Some Boosting Methods: Computational Guarantees and Connections to Regularization

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…

From  E. Cornelius 30 plays

ORIE Colloquium on 2/6/2014 - Po-Ling Loh (Cal-Berkeley): Nonconvex Methods for High-Dimensional Regression with Noisy and Missing Data

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…

From  E. Cornelius 62 plays

ORIE Colloquium, on 4/8/2014 - Cynthia Rudin: Methods for Interpretable Machine Learning

Tuesday, April 8, 2014, 253 Rhodes Hall Abstract: It is extremely important in many application domains to have transparency in predictive modeling. Domain experts do not tend to prefer "black…

From  E. Cornelius 33 plays

CAM Colloquium: Robin Snyder (Case Western) - Living in a variable environment: when should organisms hedge their bets and when should they go for broke?

Friday, March 21, 2014 at 3:30pm Frank H. T. Rhodes Hall, 655 CAM Colloquium: Robin Snyder (Case Western) - Living in a variable environment: when should organisms hedge their bets and when should…

From  E. Cornelius 25 plays