1 School of Management, Wuhan University of Science and Technology, Wuhan, China 2 School of Management, Wuhan Technology and Business University, Wuhan, China Amid the unprecedented wave of AI ...

In the '8_sgd_vs_gd' folder, the 'gd_and_sgd.ipynb' file, there is a logic flaw in the Stochastic Gradient Descent code, Since for SGD, it uses 1 randomly selected training example per epoch, rather ...

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...

ABSTRACT: In this paper, we consider a more general bi-level optimization problem, where the inner objective function is consisted of three convex functions, involving a smooth and two non-smooth ...

Quantum state tomography (QST) is a widely employed technique for characterizing the state of a quantum system. However, it is plagued by two fundamental challenges: computational and experimental ...

This repository contains the official PyTorch implementation for Grams optimizer. We introduce Gradient Descent with Adaptive Momentum Scaling (Grams), a novel optimization algorithm that decouples ...

Abstract: Based on the total least-squares (TLS) model, the gradient-descent TLS Euclidean direction search (GD-TLS-EDS) algorithm is proposed when both input and output signals are corrupted by ...