PHYS-642: Statistical physics for optimization & learning

MOOCs associés (20)

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Introduction to Discrete Choice Models

The course introduces the theoretical foundations to choice modeling and describes the steps of operational modeling.

Introduction to Discrete Choice Models

The course introduces the theoretical foundations to choice modeling and describes the steps of operational modeling.

Selected Topics on Discrete Choice

Discrete choice models are used extensively in many disciplines where it is important to predict human behavior at a disaggregate level. This course is a follow up of the online course “Introduction t

Selected Topics on Discrete Choice

Optimization: principles and algorithms - Linear optimization

Introduction to linear optimization, duality and the simplex algorithm.

Optimization: principles and algorithms - Linear optimization

Introduction to linear optimization, duality and the simplex algorithm.

Optimization: principles and algorithms - Network and discrete optimization

Introduction to network optimization and discrete optimization

Optimization: principles and algorithms - Network and discrete optimization

Introduction to network optimization and discrete optimization

Optimization: principles and algorithms - Unconstrained nonlinear optimization

Introduction to unconstrained nonlinear optimization, Newton’s algorithms and descent methods.

Optimization: principles and algorithms - Unconstrained nonlinear optimization

Introduction to unconstrained nonlinear optimization, Newton’s algorithms and descent methods.

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