17 citations · 29 across the 10 of their papers we have counts for
10 papers
Bagging cross-validated bandwidths with application to Big Data
Daniel Barreiro-Ures, Ricardo Cao, Mario Francisco Fernández +1
Hall and Robinson (2009) proposed and analyzed the use of bagged cross-validation to choose the bandwidth of a kernel density estimator. They established that bagging greatly reduc…
Screening Methods for Classification Based on Non-parametric Bayesian Tests
Naveed Merchant, Jeffrey D. Hart
Feature or variable selection is a problem inherent to large data sets. While many methods have been proposed to deal with this problem, some can scale poorly with the number of pr…
Risk Assessment for Performance-Driven Building Design with BIM-Based Parametric Methods
Fatemeh Shahsavari, Jeffrey D. Hart, Wei Yan
A growing demand for handling uncertainties and risks in performance-driven building design decision-making has challenged conventional design methods. Thus, researchers in this fi…
Estimating the Mean and Variance of a High-dimensional Normal Distribution Using a Mixture Prior
Shyamalendu Sinha, Jeffrey D. Hart
This paper provides a framework for estimating the mean and variance of a high-dimensional normal density. The main setting considered is a fixed number of vector following a high-…
Partitioned Cross-Validation for Divide-and-Conquer Density Estimation
Anirban Bhattacharya, Jeffrey D. Hart
We present an efficient method to estimate cross-validation bandwidth parameters for kernel density estimation in very large datasets where ordinary cross-validation is rendered hi…
Theoretical Properties and Practical Performance of Fully Robust One-Sided Cross-Validation
Olga Y. Savchuk, Jeffrey D. Hart
Fully robust OSCV is a modification of the OSCV method that produces consistent bandwidth in the cases of smooth and nonsmooth regression functions. The current implementation of t…