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EPFLx: Optimization: principles and algorithms - Unconstrained nonlinear optimization
Introduction to unconstrained nonlinear optimization, Newton’s algorithms and descent methods.
₹4897
This Course Includes
edx
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6 weeks at 6-8 hours per week
english
Online - Self Paced
course
EPFLx
About EPFLx: Optimization: principles and algorithms - Unconstrained nonlinear optimization
Introduction to unconstrained nonlinear optimization, Newton’s algorithms and descent methods.
What You Will Learn?
- Formulation: you will learn from simple examples how to formulate, transform and characterize an optimization problem. .
- Objective function: you will review the mathematical properties of the objective function that are important in optimization..
- Optimality conditions: you will learn sufficient and necessary conditions for an optimal solution. .
- Solving equations, Newton: this is a reminder about Newton's method to solve nonlinear equations..
- Newton's local method: you will see how to interpret and adapt Newton's method in the context of optimization..
- Descent methods: you will learn the family of descent methods, and its connection with Newton's method..