Sara Shashaani Department of Industrial and Systems Engineering North Carolina State University Title:Â Adaptive Sampling with Trust-region Optimization for Nonconvex Stochastic Functions. Abstract:Â Simulation Optimization problems are often non-convex, derivative-free, and with stochastic noise that may be notably heteroskedastic. There is … Read more
Time: Apr 5, 2024 02:00 PM Eastern Time (US and Canada) Join Zoom Meeting https://unc.zoom.us/j/95328502600?pwd=M1N4Q0ZZaXB1OXJ4WVdDeUVRbXNEUT09 Meeting ID: 953 2850 2600 Passcode: 948315 Title: Local weak limits for random digraphs Under the direction of: Dr. Sayan Banerjee and Dr. Mariana Olvera-Cravioto … Read more
Generative modeling with trees and recursive partitions Trees and recursive partitions are most well-known in supervised learning for predictive tasks, such as regression and classification. Famous examples include CART and its various forms of ensembles—e.g., random forest and boosting. A … Read more
Grigory Terlov Department of Statistics and Operations Research University of North Carolina at Chapel Hill Title: Random optimization problems at fixed temperatures Abstract: We consider a class of disordered mean-field combinatorial optimization problems, focusing on the Gibbs measure, where … Read more
Mike Baiocchi Department of Epidemiology and Population Health Stanford University
Baris Ata Operations Management University of Chicago Booth School of Business
Unbiased Estimators from Biased Algorithms In many Monte Carlo settings, one wishes to compute the expectation of a stochastic object that can only be approximated. In such settings, the natural Monte Carlo estimator will be biased. In work of McLeish … Read more
SAIL Speaker Series presents: Women in Sports Analytics A conversation in sports analytics from the perspectives of four women from different backgrounds with unique contributions to the field.       Students will … Read more
Statistical Inference for Markov Chains with Known Structure In this talk, we will discuss nonparametric estimation for Markov chains that satisfy stochastic recursions of a known form, but in which the driving noise has an unknown distribution. We assume that … Read more
