no code implementations • 19 Jul 2023 • Aaron Fisher
Many methods for estimating conditional average treatment effects (CATEs) can be expressed as weighted pseudo-outcome regressions (PORs).
no code implementations • 28 Jun 2022 • Congyu Wu, Aaron Fisher, David Schnyer
In this article we propose and validate an unsupervised probabilistic model, Gaussian Latent Dirichlet Allocation (GLDA), for the problem of discrete state discovery from repeated, multivariate psychophysiological samples collected from multiple, inherently distinct, individuals.
no code implementations • 15 Oct 2021 • Aaron Fisher
These three methods have been shown to provide online control of the "modified" false discovery rate (mFDR) under a condition known as conditional superuniformity.
no code implementations • 4 Oct 2021 • Aaron Fisher
Online testing procedures aim to control the extent of false discoveries over a sequence of hypothesis tests, allowing for the possibility that early-stage test results influence the choice of hypotheses to be tested in later stages.
no code implementations • 28 Apr 2021 • Aaron Fisher
Given any initial moving window model, these features can be defined recursively, allowing for straightforward optimization of rescoring rules.
3 code implementations • 4 Jan 2018 • Aaron Fisher, Cynthia Rudin, Francesca Dominici
Expanding on MR, we propose Model Class Reliance (MCR) as the upper and lower bounds on the degree to which any well-performing prediction model within a class may rely on a variable of interest, or set of variables of interest.
Methodology
no code implementations • 5 May 2014 • Aaron Fisher, Brian Caffo, Brian Schwartz, Vadim Zipunnikov
As a result, all bootstrap principal components are limited to the same $n$-dimensional subspace and can be efficiently represented by their low dimensional coordinates in that subspace.
Methodology Applications Computation