Optimization

Steven L. Brunton is the Boeing AI and Data-Driven Engineering Professor of Mechanical Engineering at the University of Washington, where he is the Director of the NSF AI Institute in Dynamic Systems and the Director of the AI Center for Dynamics and Control. His research has been recognized with awards including the Presidential Early Career Award for Scientists and Engineers. Steve is also passionate about teaching math to engineers as an author of five textbooks and through his popular YouTube channel, 'eigensteve'.

• Preface; Acknowledgments; 1. Optimization bootcamp; 2. Gradient based optimization; 3. Linear programming; 4. Least-squares regression; 5. Nonsmooth and global optimization; 6. Constraints and duality; 7. Bayesian modeling and estimation; 8. Optimization for inverse problems; 9. Optimization for control; 10. Optimization for machine learning; Glossary; Bibliography.

'Steve Brunton explores optimization with clarity and ambition. Throughout, the book maintains an excellent balance between mathematical insight and practical implementation, with well-chosen examples and Python code that illuminate what is happening beneath the algorithmic surface. This is an accessible text for readers encountering the material for the first time and a valuable reference for researchers wanting to study one of the topics presented in greater depth.' Richard Murray, Caltech