We consider the problem of modeling the mean function in regression. Often there is enough knowledge to model some components of the mean function parametrically. But for other vague and/or nuisance ...

Computational methods for fitting nonlinear models have developed considerably in the last decade. Statistical use of these techniques has, as yet, lagged somewhat behind. The present paper gives a ...

In today's machine learning field, deep neural network models are becoming increasingly large and complex, posing significant challenges to traditional electronic computing hardware. To address this ...

SHENZHEN, China, May 12, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, announced the development of a groundbreaking ...

Highly reduced order models with nonlinear contact – extremely efficient computation. Modeled as linear components interconnected with highly reduced-order components. 1-linear reduced model, ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

Effectiveness of Adjuvant Chemotherapy After Radical Nephroureterectomy for Locally Advanced and/or Positive Regional Lymph Node Upper Tract Urothelial Carcinoma This analysis included 502,321 ...