Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Are two sets of data genuinely different, or is it because of randomness? This question, known as the two-sample testing problem, becomes notoriously difficult in modern datasets, because they are ...

In 2026, Azure Machine Learning has evolved from a sandbox for data scientists into a robust platform for operational forecasting, yet many teams still struggle to see what happens after deployment.

Abstract: The debiased estimator is a crucial tool in statistical inference for high-dimensional model parameters. However, constructing such an estimator involves estimating the high-dimensional ...

A significant shift is under way in artificial intelligence, and it has huge implications for technology companies big and small. For the past half-decade, most of the focus in AI has been on training ...

The creators of the open source project vLLM have announced that they transitioned the popular tool into a VC-backed startup, Inferact, raising $150 million in seed funding at an $800 million ...

Purdue University’s online Master's in Applied Statistics prepares students to advance theory, methods and computing for the purpose of meeting today’s emerging science and technology by including ...

ABSTRACT: Special education services are designed to provide tailored support for students with diverse learning needs, with the expectation of improving academic achievement. This study examines the ...

The research fills a gap in standardized guidance for lipidomics/metabolomics data analysis, focusing on transparency and reproducibility using R and Python. The approach offers modular, interoperable ...