In 2026, tech leaders are learning a painful lesson: the problem with scaling AI adoption isn't understanding the algorithm, ...
In recent years, artificial intelligence has become more accessible than ever before. Powerful libraries, automated platforms ...
Abstract: A crucial task in predictive maintenance is estimating the remaining useful life of physical systems. In the last decade, deep learning has improved considerably upon traditional model-based ...
Government-funded academic research on parallel computing, stream processing, real-time shading languages, and programmable ...
Those changes will be contested, in math as in other academic disciplines wrestling with AI’s impact. As AI models become a ...
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How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?
Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
High-temperature proton exchange membrane fuel cells (HT-PEMFCs) are highly promising for next-generation aviation, as they can operate above 160 °C and tolerate impurities in the fuel. However, they ...
ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
Abstract: Online first-order algorithms for function identification and regression with noisy data often rely on replacing actual gradients with their constructed noisy estimates. Stochastic gradient ...
ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
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