Machine learning is an integral part of high-stakes decision-making in a broad swath of human-computer interactions. You ...

Early-warning signs of marsh decline provided by the model could be crucial for conservation. “Once [marsh] loss occurs, that ...

Probability and Statistics Group research at the School of Mathematical and Computer Sciences at Heriot-Watt University, Edinburgh.

Just as people from different countries speak different languages, AI models also create various internal "languages"—a ...

A machine learning algorithm for a low-speed primary coding algorithm based on automatic recognition of speech signal fragments (SS) using hidden Markov models (HMM) has been developed. When assessing ...

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help ...

Finding relationships between bio-signals and health outcomes is complicated for many reasons, including sorting out irrelevant data.

In this paper, we propose a machine learning-based automated framework for algorithm selection and configuration for MPC applications. This framework aids the online implementation of MPC by selecting ...

This study presents a theoretical framework that models LLMs as Markov chains, offering a structured approach to understanding their inference mechanisms. By deriving generalization bounds and ...