Cross-validation (CV) is a widely adopted approach for selecting the optimal model.
However, the computation of empirical cross-validation error (CVE) has high complexity due …

Over-the-Air (OTA) computation is the problem of computing functions of distributed data
without transmitting the entirety of the data to a central point. By avoiding such costly …

While studies in metamodel-assisted optimization predominantly involve continuous
variables, this paper explores the additional presence of categorical data, representing for …

We study the problem of preferential Bayesian optimization (BO), where we aim to optimize
a black-box function with only preference feedback over a pair of candidate solutions …

Cross-selling is an integral component of customer relationship management. Using
relevant information to improve customer response rate is a challenging task in cross-selling …

A family of learning algorithms generated from additive models have attracted much
attention recently for their flexibility and interpretability in high dimensional data analysis …

In this work, we investigate a unique solvability of a direct and inverse source problem for a
time-fractional partial differential equation with the Caputo and Bessel operators. Using …

This study develops a learning-simulation coordinated method to perform individual-level
causal inference and social influence identification in social media. This method uses …

A novel optimization framework for boiler combustion and selective catalytic reduction
systems (BCSCRSs) that accounts for flue gas temperature deviation and integrates prior …

Additive models play an important role in semiparametric statistics. This paper gives
learning rates for regularized kernel-based methods for additive models. These learning …