Tabular artificial intelligence startup Prior Labs GmbH today announced a new foundation model that can handle millions of rows of data to give enterprises a way to understand and use their most ...

SAP aims to displace more general large language models with the release of its own foundational “tabular” model, which the company claims will reduce training requirements for enterprises. The model, ...

Abstract: Generative Adversarial Network (GAN) models have shown to be effective in a wide range of machine learning applications, and tabular data generation process has not been an exception.

Abstract: In recent years, numerous model extraction attacks have been proposed to investigate the potential vulnerabilities of tabular models. However, applying these attacks in real-world scenarios ...

Regression tasks, which involve predicting continuous numeric values, have traditionally relied on numeric heads such as Gaussian parameterizations or pointwise tensor projections. These traditional ...

Say you run a hospital and you want to estimate which patients have the highest risk of deterioration so that your staff can prioritize their care 1. You create a spreadsheet in which there is a row ...

Machine learning for predictive modeling aims to forecast outcomes based on input data accurately. One of the primary challenges in this field is “domain adaptation,” which addresses differences ...

ABSTRACT: Through analyzing the problems of the Swiss Cheese Model theory and the Energy Theory, this paper combines the two kinds of theories after modifying them for the first time, and a new ...