Abstract: In this article, we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems ...

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

Stochastic modelling is the development of mathematical models for non-deterministic physical systems, which can adopt many possible behaviours starting from any given initial condition. Monte-Carlo ...

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: This article is devoted to stochastic convergence theorems for stochastic impulsive systems (SISs) and their application to discrete-time stochastic feedback control (DTSFC). A general ...

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 ...

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 ...

gollm is a Go package designed to help you build your own AI golems. Just as the mystical golem of legend was brought to life with sacred words, gollm empowers you to breathe life into your AI ...