Abstract: This article introduces an innovative motion planning algorithm for autonomous mobile robots, specifically focusing on quadrotor unmanned aerial vehicles (UAVs), utilizing a gradient descent ...

Abstract: The gradient descent bit-flipping with momentum (GDBF-w/M) and probabilistic GDBF-w/M (PGDBF-w/M) algorithms significantly improve the decoding performance of the bit-flipping (BF) algorithm ...

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: Dynamic image degradations, including noise, blur and lighting inconsistencies, pose significant challenges in image restoration, often due to sensor limitations or adverse environmental ...

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 ...

1 Department of Mathematics, University of Ndjamena, Ndjamena, Tchad. 2 Department of Mathematics and Computer Science, University of Cheikh. A. Diop, Dakar, Senegal. In the evolving landscape of ...

We’re asking unanswered questions for her potential administration. By David Leonhardt Kamala Harris has largely avoided answering questions since her campaign began: She hasn’t participated in a town ...