MATH-261: Discrete optimizationThis course is an introduction to linear and discrete optimization.
Warning: This is a mathematics course! While much of the course will be algorithmic in nature, you will still need to be able to p
MATH-512: Optimization on manifoldsWe develop, analyze and implement numerical algorithms to solve optimization problems of the form min f(x) where x is a point on a smooth manifold. To this end, we first study differential and Riemann
CS-455: Topics in theoretical computer scienceThe students gain an in-depth knowledge of several current and emerging areas of theoretical computer science. The course familiarizes them with advanced techniques, and develops an understanding of f
MGT-418: Convex optimizationThis course introduces the theory and application of modern convex optimization from an engineering perspective.
PHYS-435: Statistical physics IIIThis course introduces statistical field theory, and uses concepts related to phase transitions to discuss a variety of complex systems (random walks and polymers, disordered systems, combinatorial o
MATH-600: Optimization and simulationMaster state-of-the art methods in optimization with heuristics and simulation.
Work involves:
- reading the material beforehand
- class hours to discuss the material and solve problems
- homework
MGT-483: Optimal decision makingThis course introduces the theory and applications of optimization. We develop tools and concepts of optimization and decision analysis that enable managers in manufacturing, service operations, marke
