Ansgar Steland | DeepAI

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∙ 02/14/2023

Online Detection of Changes in Moment-Based Projections: When to Retrain Deep Learners or Update Portfolios?

Sequential monitoring of high-dimensional nonlinear time series is studi...

0 Ansgar Steland, et al. ∙

∙ 11/04/2022

Projection inference for high-dimensional covariance matrices with structured shrinkage targets

Analyzing large samples of high-dimensional data under dependence is a c...

0 Fabian Mies, et al. ∙

∙ 03/07/2022

Sequential Gaussian approximation for nonstationary time series in high dimensions

Gaussian couplings of partial sum processes are derived for the high-dim...

0 Fabian Mies, et al. ∙

∙ 01/06/2021

Cross-Validation and Uncertainty Determination for Randomized Neural Networks with Applications to Mobile Sensors

Randomized artificial neural networks such as extreme learning machines ...

0 Ansgar Steland, et al. ∙

∙ 09/13/2020

Is there a role for statistics in artificial intelligence?

The research on and application of artificial intelligence (AI) has trig...

0 Sarah Friedrich, et al. ∙

∙ 05/22/2020

Extreme Learning and Regression for Objects Moving in Non-Stationary Spatial Environments

We study supervised learning by extreme learning machines and regression...

0 Ansgar Steland, et al. ∙

∙ 01/15/2020

Detecting Changes in the Second Moment Structure of High-Dimensional Sensor-Type Data in a K-Sample Setting

The K sample problem for high-dimensional vector time series is studied,...

0 Nils Mause, et al. ∙

∙ 12/10/2019

Testing and Estimating Change-Points in the Covariance Matrix of a High-Dimensional Time Series

This paper studies methods for testing and estimating change-points in t...

0 Ansgar Steland, et al. ∙

∙ 10/07/2019

High-Confident Nonparametric Fixed-Width Uncertainty Intervals and Applications to Projected High-Dimensional Data and Common Mean Estimation

Nonparametric two-stage procedures to construct fixed-width confidence i...

0 Yuan-Tsung Chang, et al. ∙

∙ 09/03/2018

Shrinkage for Covariance Estimation: Asymptotics, Confidence Intervals, Bounds and Applications in Sensor Monitoring and Finance

When shrinking a covariance matrix towards (a multiple) of the identity ...

0 Ansgar Steland, et al. ∙

∙ 07/26/2018

Automatic Processing and Solar Cell Detection in Photovoltaic Electroluminescence Images

Electroluminescence (EL) imaging is a powerful and established technique...

0 Evgenii Sovetkin, et al. ∙

∙ 04/28/2018

On Convergence of Moments for Approximating Processes and Applications to Surrogate Models

We study critera for a pair ({ X_n } , { Y_n }) of approximating proc...

0 Ansgar Steland, et al. ∙

∙ 11/06/2017

Asymptotics for high-dimensional covariance matrices and quadratic forms with applications to the trace functional and shrinkage

We establish large sample approximations for an arbitray number of bilin...

0 Ansgar Steland, et al. ∙

∙ 10/05/2017

Jackknife variance estimation for common mean estimators under ordered variances and general two-sample statistics

Samples with a common mean but possibly different, ordered variances ari...

0 Ansgar Steland, et al. ∙

∙ 01/12/2010

A Binary Control Chart to Detect Small Jumps

The classic N p chart gives a signal if the number of successes in a seq...

0 Ansgar Steland, et al. ∙

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