Understanding the benefits of matrix converters for EV chargers and a comparison of different matrix converter topologies.

Abstract: High-dimensional and incomplete (HDI) matrices are commonly encountered in various big data-related applications for illustrating the complex interactions among numerous entities, like the ...

Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), Italian National Research Council (CNR), Milan, Italy Introduction: In neuroscience, the muscle ...

ABSTRACT: In this paper, an Optimal Predictive Modeling of Nonlinear Transformations “OPMNT” method has been developed while using Orthogonal Nonnegative Matrix Factorization “ONMF” with the ...

CNBC's Squawk Box Asia Martin Soong and Chery Kang talk about AMD's chip supply deal with OpenAI, plus the web of alliances, cross shareholdings and the money loop that could shape the AI space. Major ...

Collaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items. To predict scores for unrated items, matrix ...

The goal in nonnegative matrix factorization (NMF) is to express, exactly or approximately, a given matrix as a product of two nonnegative matrices of smaller inner dimension. NMFs arise naturally in ...

ABSTRACT: Variational methods are highly valuable computational tools for solving high-dimensional quantum systems. In this paper, we explore the effectiveness of three variational methods: density ...

Abstract: Recommender systems (RSs) are useful technology that can alleviate the problem of overload of information provided to users. In this research, we build a new RS, and we name it ETagMF.

As Machine Learning (ML) applications rapidly grow, concerns about adversarial attacks compromising their reliability have gained significant attention. One unsupervised ML method known for its ...