181 citations · 230 across the 5 of their papers we have counts for
7 papers
Projected Regression Methods for Inverting Fredholm Integrals: Formalism and Application to Analytical Continuation
Louis-Francois Arsenault, Richard Neuberg, Lauren A. Hannah +1
We present a machine learning approach to the inversion of Fredholm integrals of the first kind. The approach provides a natural regularization in cases where the inverse of the Fr…
Ensemble Methods for Convex Regression with Applications to Geometric Programming Based Circuit Design
Lauren Hannah, David Dunson
Convex regression is a promising area for bridging statistical estimation and deterministic convex optimization. New piecewise linear convex regression methods are fast and scalabl…
Beta-Negative Binomial Process and Poisson Factor Analysis
Mingyuan Zhou, Lauren Hannah, David Dunson +1
A beta-negative binomial (BNB) process is proposed, leading to a beta-gamma-Poisson process, which may be viewed as a "multi-scoop" generalization of the beta-Bernoulli process. Th…
Bayesian nonparametric multivariate convex regression
Lauren A. Hannah, David B. Dunson
In many applications, such as economics, operations research and reinforcement learning, one often needs to estimate a multivariate regression function f subject to a convexity con…
Multivariate convex regression with adaptive partitioning
Lauren A. Hannah, David B. Dunson
We propose a new, nonparametric method for multivariate regression subject to convexity or concavity constraints on the response function. Convexity constraints are common in econo…
Stochastic Search with an Observable State Variable
Lauren A. Hannah, Warren B. Powell, David M. Blei
In this paper we study convex stochastic search problems where a noisy objective function value is observed after a decision is made. There are many stochastic search problems whos…