Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, ...

Abstract: Microwave device design increasingly relies on surrogate modeling to accelerate optimization and reduce costly electromagnetic (EM) simulations. This article presents a spectral Bayesian ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

Abstract: In this work, we propose a framework for adapting the controller's parameters based on learning optimal solutions from contextual black-box optimization problems. We consider a class of ...

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Gordon Scott has been an active investor and ...

We will keep our notes and code on dealing with censored variables in Bayesian models in this repo. My initial idea for this is that we can basically treat each worked out example or section that we ...

In this tutorial, we shift from traditional prompt crafting to a more systematic, programmable approach by treating prompts as tunable parameters rather than static text. Instead of guessing which ...

A comprehensive tutorial repository for learning deep learning model optimization techniques, including network tuning, backpropagation optimization, overfitting management, and root cause analysis.