2.5k citations · 3.6k across the 46 of their papers we have counts for
29 papers · 1 filter
From Thomas Bayes to Big Data: On the feasibility of being a subjective Bayesian
Ya'acov Ritov
We argue that the Bayesian paradigm, of a prior which represents the beliefs of the statistician before observing the data, is not feasible in ultra-high-dimensional models. We cla…
Distributional Robustness and Transfer Learning Through Empirical Bayes
Michael Law, Peter Bühlmann, Ya'acov Ritov
We consider the problem of statistical inference on parameters of a target population when auxiliary observations are available from related populations. We propose a flexible empi…
Rank-Constrained Least-Squares: Prediction and Inference
Michael Law, Ya'acov Ritov, Ruixiang Zhang +1
In this work, we focus on the high-dimensional trace regression model with a low-rank coefficient matrix. We establish a nearly optimal in-sample prediction risk bound for the rank…
High-Dimensional Varying Coefficient Models with Functional Random Effects
Michael Law, Ya'acov Ritov
We consider a sparse high-dimensional varying coefficients model with random effects, a flexible linear model allowing covariates and coefficients to have a functional dependence w…
Generalized maximum likelihood estimation of the mean of parameters of mixtures, with applications to sampling
Eitan Greenshtein, Ya'acov Ritov
Let be a parametric family, a given function, and an unknown mixing distribution. It is desired to estimate based on independe…
On robust learning in the canonical change point problem under heavy tailed errors in finite and growing dimensions
Debarghya Mukherjee, Moulinath Banerjee, Ya'acov Ritov
This paper presents a number of new findings about the canonical change point estimation problem. The first part studies the estimation of a change point on the real line in a simp…