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Gradient descent from scratch in Python – step by step tutorial

Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple. Trump pulls US out of more than 30 UN bodies ICE shooting ...
Scientific Research Publishing

Ruder, S. (2016) An Overview of Gradient Descent Optimization Algorithms. arXiv Preprint.

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
JSTOR Daily

Scalable statistical inference for averaged implicit stochastic gradient descent

Stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates in applications involving large-scale data or streaming data. As an alternative version, averaged implicit SGD ...
IEEE

Consensus-Based Distributed Optimization for Multiagent Systems Over Multiplex Networks

Abstract: Multilayer networks provide a more comprehensive framework for exploring real-world and engineering systems than traditional single-layer networks consisting of multiple interacting networks ...
IEEE

IRKA Is a Riemannian Gradient Descent Method

Abstract: The iterative rational Krylov algorithm (IRKA) is a commonly used fixed point iteration developed to minimize the $\mathcal {H}_{2}$ model order reduction ...
Frontiers

Identification of Orphan Genes in Unbalanced Datasets Based on Ensemble Learning

Orphan genes are associated with regulatory patterns, but experimental methods for identifying orphan genes are both time-consuming and expensive. Designing an accurate and robust classification model ...
insideHPC

RMSprop Optimization Algorithm for Gradient Descent with Neural Networks

A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...