Optimization Bootcamp: Convex Optimization for ML & Control · Lec 4·Convexity, Duality & Linear Programming · Steve Brunton · University of Washington
14:58
Linear algebra, real and complex analysis, topology, differential geometry, probability, combinatorics, and number theory.
Structural connections linking subfields, mathematical foundations, and courses across disciplines.
MIT · 43 lectures
Strang's foundational work in linear algebra provides essential tools for understanding and solving problems in convex optimization, particularly in areas like least squares and matrix decompositions.
University of Washington · Steve Brunton
This bootcamp provides a practical yet rigorous introduction to convex optimization, covering core concepts like convex sets, functions, duality, and algorithms, which are fundamental to the subfield and its applications.