Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.
Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.
Explores finite dimensional spaces, covering extraction process, bases generation, and space completion.
Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
