Streaming variational bayes
We present SDA-Bayes, a framework for (S) treaming,(D) istributed,(A) synchronous
computation of a Bayesian posterior. The framework makes streaming updates to the …
computation of a Bayesian posterior. The framework makes streaming updates to the …
[HTML][HTML] Statistical inference for the mean outcome under a possibly non-unique optimal treatment strategy
AR Luedtke, MJ Van Der Laan - Annals of statistics, 2016 - ncbi.nlm.nih.gov
We consider challenges that arise in the estimation of the mean outcome under an optimal
individualized treatment strategy defined as the treatment rule that maximizes the population …
individualized treatment strategy defined as the treatment rule that maximizes the population …
Anomaly detection in streaming nonstationary temporal data
This article proposes a framework that provides early detection of anomalous series within a
large collection of nonstationary streaming time-series data. We define an anomaly as an …
large collection of nonstationary streaming time-series data. We define an anomaly as an …
Fast approximate inference for arbitrarily large semiparametric regression models via message passing
MP Wand - Journal of the American Statistical Association, 2017 - Taylor & Francis
We show how the notion of message passing can be used to streamline the algebra and
computer coding for fast approximate inference in large Bayesian semiparametric …
computer coding for fast approximate inference in large Bayesian semiparametric …
Principal weighted least square support vector machine: An online dimension-reduction tool for binary classification
HJ Jang, SJ Shin, A Artemiou - Computational Statistics & Data Analysis, 2023 - Elsevier
As relevant technologies advance, streamed data are frequently encountered in various
applications, and the need for scalable algorithms becomes urgent. In this article, we …
applications, and the need for scalable algorithms becomes urgent. In this article, we …
Real-time sufficient dimension reduction through principal least squares support vector machines
We propose a real-time approach for sufficient dimension reduction. Compared with popular
sufficient dimension reduction methods including sliced inverse regression and principal …
sufficient dimension reduction methods including sliced inverse regression and principal …
Variational inference for count response semiparametric regression
Fast variational approximate algorithms are developed for Bayesian semiparametric
regression when the response variable is a count, ie, a non-negative integer. We treat both …
regression when the response variable is a count, ie, a non-negative integer. We treat both …
Real-time regression with dividing local Gaussian processes
The increased demand for online prediction and the growing availability of large data sets
drives the need for computationally efficient models. While exact Gaussian process …
drives the need for computationally efficient models. While exact Gaussian process …
Laplace approximations for fast Bayesian inference in generalized additive models based on P-splines
O Gressani, P Lambert - Computational Statistics & Data Analysis, 2021 - Elsevier
Generalized additive models (GAMs) are a well-established statistical tool for modeling
complex nonlinear relationships between covariates and a response assumed to have a …
complex nonlinear relationships between covariates and a response assumed to have a …