Views Navigation

Event Views Navigation

Estimation of Functionals of High-Dimensional and Infinite-Dimensional Parameters of Statistical Models

Vladimir Koltchinskii (Georgia Institute of Technology)
2-449

The mini-course will meet on Monday, April 1 and Wednesday, April 3rd from 1:30-3:00pm This mini-course deals with a circle of problems related to estimation of real valued functionals of high-dimensional and infinite-dimensional parameters of statistical models. In such problems, it is of interest to estimate one-dimensional features of a high-dimensional parameter represented by nonlinear functionals of certain degree of smoothness defined on the parameter space. The functionals of interest could be often estimated with faster convergence rates than the…

Find out more »

Optimal nonparametric capture-recapture methods for estimating population size

Edward Kennedy (Carnegie Mellon University)
E18-304

Abstract: Estimation of population size using incomplete lists has a long history across many biological and social sciences. For example, human rights groups often construct partial lists of victims of armed conflicts, to estimate the total number of victims. Earlier statistical methods for this setup often use parametric assumptions, or rely on suboptimal plug-in-type nonparametric estimators; but both approaches can lead to substantial bias, the former via model misspecification and the latter via smoothing. Under an identifying assumption that two lists…

Find out more »

Matrix displacement convexity and intrinsic dimensionality

Yair Shenfeld (Brown University)
E18-304

Abstract: The space of probability measures endowed with the optimal transport metric has a rich structure with applications in probability, analysis, and geometry. The notion of (displacement) convexity in this space was discovered by McCann, and forms the backbone of this theory.  I will introduce a new, and stronger, notion of displacement convexity which operates on the matrix level. The motivation behind this definition is to capture the intrinsic dimensionality of probability measures which could have very different behaviors along…

Find out more »


MIT Institute for Data, Systems, and Society
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139-4307
617-253-1764