Covers gradient line search methods and optimization techniques with an emphasis on Wolfe conditions and positive definiteness.
Covers the LLL algorithm for reducing lattice bases to shorter and more orthogonal forms through iterative transformations.
Explores fundamental groups, homotopy classes, and coverings in connected manifolds.
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.
Covers the LLL algorithm for lattice reduction and discusses Hermite's constant and Minkowski's theorem.
Covers unconstrained and constrained optimization, optimal control, neural networks, and global optimization methods.
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.
