Leon Bottou. Online learning and stochastic approximations. In D Saad, editor, Online Algorithms and Stochastic Approximations. Cambridge University Press, Cambridge, U.K., 1998.
Events
Interdisciplinary Seminar: Fan Li, Duke University
“Overlap Weighting for Causal Inference,” presented by Dr. Fan Li, Duke University
Interdisciplinary Seminar: Susan Murphy, Harvard University
“Assessing Personalization in Digital Health,” presented by Dr. Susan Murphy, Harvard University
An Introduction to the UConn Statistics Cluster (September 13, 2021)
All faculty and graduate students in the Department of Statistics are invited. Time: September 13, 3:35 pm to 4:25 pm Place: AUST 103 Speaker: Daniel Prather, Administrator for the Statistics Computer Cluster Title: An Introduction to the UConn Statistics Cluster
Paper of the Month: September 2021
Rubin, D. B. (1976). Inference and missing data. Biometrika, 63(3), 581-592., Cambridge, U.K., 1998.
Interdisciplinary Seminar: Jon Krosnick, Stanford University
“The Collapse of Scientific Standards in the World of High Visibility Survey Research,” presented by Dr. Jon Krosnick, Stanford University
Interdisciplinary Seminar: David Kaplan, University of Wisconsin-Madison
“Developments and Extensions in the Quantification of Model Uncertainty: A Bayesian Perspective,” presented by David Kaplan, University of Wisconsin-Madison
Interdisciplinary Seminar: Jennifer Hill, Columbia University
“thinkCausal: One Stop Shopping for Answering your Causal Inference Questions,” presented by Jennifer Hill, Columbia University
Interdisciplinary Seminar: Jean-Paul Fox, University of Twente
“Bayesian Covariance Structure Modeling: An Overview and New Developments,” presented by Jean-Paul Fox, University of Twente
Interdisciplinary Seminar: Susan Paddock, NORC at the University of Chicago
“Causal Inference Under Interference in Dynamic Therapy Group Studies,” presented by Dr. Susan Paddock, NORC University of Chicago