Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind ...

Abstract: Distributed weakly convex optimization is a significant class of problems in signal and information processing, with wide-ranging applications such as sparse dictionary learning, low-rank ...

Abstract: Distribution network optimization is represented by non-convex power flow equations, where traditional convex relaxation methods may lead to inaccurate or infeasible solutions. To ...

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 ...

James Chen, CMT is an expert trader, investment adviser, and global market strategist. Cierra Murry is an expert in banking, credit cards, investing, loans, mortgages, and real estate. She is a ...

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

A lightweight neural network inference engine focused on GEMM (General Matrix Multiply) optimization. This project demonstrates progressive optimization techniques to achieve high-performance matrix ...