Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more. IEEE Keywords Pervasive computing , Adaptive learning , Accuracy , Social networking ...

In the era of Artificial Intelligence and Machine Learning, data analysis is attracting higher attention in different areas which include finance, healthcare, w ...

Journal of Nuclear Medicine Technology August 2025, jnmt.125.269869; DOI: https://doi.org/10.2967/jnmt.125.269869 ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing ...

In the original published article, there were typographical errors in mathematical formulas (Equations 58, 59, 73, and 74). The equations were derived and implemented correctly in the computer program ...

ABSTRACT: We introduce the Kernel-based Partial Conditional Mean Dependence, a scalar-valued measure of conditional mean dependence of Y given X , while adjusting for the nonlinear dependence on Z .

Fujian Key Laboratory of Agricultural Information Sensor Technology, College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China Center ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...