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Mini-batch gradient descent in deep learning explained

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...
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 ...
Yahoo

FULL SPEECH: Zohran Mamdani's victory speech following historic NYC mayoral win

Democrat Zohran Mamdani delivers his winning remarks after a projected win of the New York City mayoral election. He is set to be the first the city's Muslim mayor of South Asian descent. Could Mo ...
IEEE

LCoopPG: Deep unfolding-assisted fully distributed MIMO detection algorithm

Abstract: In this paper, we introduce the learned cooperative projected gradient descent (LCoopPG) algorithm for fully distributed multiple-input multiple-output (MIMO) signal detection. The proposed ...
IEEE

Projected Gradient Descent-Based Dynamic Event-Triggered Optimal Control for MVDC-DS Considering Power Interaction Ability With AC Grid

Abstract: To avoid system failures in medium-voltage DC distribution system (MVDC-DS) caused by excessive power interactions with AC grid at a modest communication burden, this paper proposes a ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of ...