Title: Statistical Mechanics on Sparse Random Graphs: Mathematical Perspective Abstract: Theoretical models of disordered materials lead to challenging mathematical problems with applications to random combinatorial problems and coding theory. The underlying structure is that of many discrete variables that are strongly interacting according to a mean field model determined by a random sparse graph. Focusing on random finite graphs that converge locally to trees we review recent progress in validating the `cavity prediction for the limiting free energy per vertex and the approximation of... Read more about CMSA Talk: Amir Dembo

Meta-Analysis by Confidence Distribution - A Unified Approach and Beyond

Exploring Objective Causal Inference in Case-Noncase Studies under the Rubin Causal Model

Causality and Statistical Learning

Two Approaches of Analyzing Functional Time Series

Optimistic Concurrency Control for Distributed Machine Learning

(cancelled)

David K. Pickard Memorial Lecture Series "The Role of Data Science in Statistics Education" Deborah Nolan, University of California, Berkeley Reception to follow from 5:30 to 6:30 PM in the lobby.

Sex, Lies and Self-Reported Counts: General Birth-Death Processes to Model Self-Reported Count of Sexual Behavior Surveys often ask respondents to report non-negative counts, but respondents may misremember or round to a nearby multiple of 5 or 10. The error inherent in this heaping can bias estimation. To avoid bias, we propose a novel reporting distribution arising from a general birth-death process whose underlying parameters are readily interpretable as rates of misremembering and rounding. The process accommodates a variety of heaping grids and allows for quasi-heaping to values nearly... Read more about HSPHBiostat: Marc Suchard

Simulated Likelihood Estimators for Discretely Observed Jump-Diffusions

Harvard Statistics Department Retreat 9:30 AM-5:00 PM. Open to anyone in the Harvard Statistics community, including (but not limited to) students of all levels, post-docs, and faculty. This full-day event---an annual tradition---will feature student and faculty panel discussions, two lectures from distinguished guests, and a statistics-themed game.

Infographics Registration required for presentation (free)

Effective Ancillarity: A Modeling-Building Principle in the Presence of Misspecification

A Bayesian Model for the Detection of X-ray Binary Black Holes

Privacy in a Networked World Fourth Annual Symposium on the Future of Computation in Science and Engineering Institute for Applied Computational Science, Harvard University