Optimization algorithms and methods
In calculus, Newton's method is an iterative method for finding the roots of a differentiable function F, which are solutions to the equation F (x) = 0. As such, Newton's method can be applied to the derivative f ′ of a twice-differentiable function f to find the roots of the derivative (solutions to f ′(x) = 0), also known as the critical points of f. These solutions may be minima, maxima, or saddle points; see section "Several variables" in Critical point (mathematics) and also section in this article. This is relevant in optimization, which aims to find (global) minima of the function f. (Wikipedia).
Visually Explained: Newton's Method in Optimization
We take a look at Newton's method, a powerful technique in Optimization. We explain the intuition behind it, and we list some of its pros and cons. No necessary background required beyond basic linear algebra and calculus. 00:00 Introduction 00:14 Unconstrained Optimization 01:18 Itera
From playlist Visually Explained
Newton's Method | Lecture 14 | Numerical Methods for Engineers
Derivation of Newton's method for root finding. Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engineers.pdf Subscribe to my channel: http://www.youtube.com/user/jchasnov?sub_confirmat
From playlist Numerical Methods for Engineers
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys How To Use Newton's Method from Calculus. An easy example using the formula.
From playlist Calculus
This video explains Newton's Method and provides an example. It also shows how to use the table feature of the graphing calculator to perform the calculations needed for Newton's Method. http://mathispower4u.wordpress.com/
From playlist Newton’s Method and L’Hopital’s Rule
[Calculus] Newton's Method || Lecture 36
Visit my website: http://bit.ly/1zBPlvm Subscribe on YouTube: http://bit.ly/1vWiRxW Hello, welcome to TheTrevTutor. I'm here to help you learn your college courses in an easy, efficient manner. If you like what you see, feel free to subscribe and follow me for updates. If you have any que
From playlist Calculus 1
Ex: Newton's Method to Approximate Zeros -- 2 Iterations
This video provides an example of how to approximate zeros or roots of a polynomial equation using Newton's Method. Two iterations are provided. Site: http://mathispower4u.com
From playlist Newton’s Method and L’Hopital’s Rule
Newton's Method for Systems of Nonlinear Equations
Generalized Newton's method for systems of nonlinear equations. Lesson goes over numerically solving multivariable nonlinear equations step-by-step with visual examples and explanation of the Jacobian, the backslash operator, and the inverse Jacobian. Example code in MATLAB / GNU Octave on
From playlist Newton's Method
Convergence of Newton's Method | Lecture 17 | Numerical Methods for Engineers
Calculation of the order of convergence of Newton's method. Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engineers.pdf Subscribe to my channel: http://www.youtube.com/user/jchasnov?s
From playlist Numerical Methods for Engineers
Jorge Nocedal: "Tutorial on Optimization Methods for Machine Learning, Pt. 1"
Graduate Summer School 2012: Deep Learning, Feature Learning "Tutorial on Optimization Methods for Machine Learning, Pt. 1" Jorge Nocedal, Northwestern University Institute for Pure and Applied Mathematics, UCLA July 19, 2012 For more information: https://www.ipam.ucla.edu/programs/summ
From playlist GSS2012: Deep Learning, Feature Learning
Jorge Nocedal: "Tutorial on Optimization Methods for Machine Learning, Pt. 3"
Graduate Summer School 2012: Deep Learning, Feature Learning "Tutorial on Optimization Methods for Machine Learning, Pt. 3" Jorge Nocedal, Northwestern University Institute for Pure and Applied Mathematics, UCLA July 18, 2012 For more information: https://www.ipam.ucla.edu/programs/summ
From playlist GSS2012: Deep Learning, Feature Learning
11. Unconstrained Optimization; Newton-Raphson and Trust Region Methods
MIT 10.34 Numerical Methods Applied to Chemical Engineering, Fall 2015 View the complete course: http://ocw.mit.edu/10-34F15 Instructor: James Swan Students learned how to solve unconstrained optimization problems. In addition of the Newton-Raphson method, students also learned the steepe
From playlist MIT 10.34 Numerical Methods Applied to Chemical Engineering, Fall 2015
Lecture 16 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, lectures on how equality constrained minimization is utilized in electrical engineering for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving co
From playlist Lecture Collection | Convex Optimization
Lecture 17 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, continues his lecture on equality constrained minimization for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization problems th
From playlist Lecture Collection | Convex Optimization
Lecture 18 | Convex Optimization I (Stanford)
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, lectures on the interior-point methods of electrical engineering and convex optimization for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving c
From playlist Lecture Collection | Convex Optimization
Jorge Nocedal: "Tutorial on Optimization Methods for Machine Learning, Pt. 2"
Graduate Summer School 2012: Deep Learning, Feature Learning "Tutorial on Optimization Methods for Machine Learning, Pt. 2" Jorge Nocedal, Northwestern University Institute for Pure and Applied Mathematics, UCLA July 19, 2012 For more information: https://www.ipam.ucla.edu/programs/summ
From playlist GSS2012: Deep Learning, Feature Learning
Harvard AM205 video 4.9 - Quasi-Newton methods
Harvard Applied Math 205 is a graduate-level course on scientific computing and numerical methods. The previous video in this series discussed using the Newton method to find local minima of a function; while this method can be highly efficient, it requires the exact Hessian of the functio
From playlist Optimizers in Machine Learning
How Newton's method solves multiple equations at once
This video explains how Newton's method (also called the Newton-Raphson method) can solve more than one equation simultaneously. MDO Lab: https://mdolab.engin.umich.edu/ Engineering Design Optimization: https://mdobook.github.io/ Animations done using Manim: https://docs.manim.community/e
From playlist Summer of Math Exposition 2 videos