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Covers exercises on the spin model, independent set, matching, and increasing functions.
Explores fundamental graph theory concepts, Erdős' results, Chromatic Lemma, and Union Bound theorem in graph theory.
Covers MAE regression, convex hull, reformulation advantages, and practical problems with decision variables and constraints.
Covers the fundamentals of Nonlinear Programming and its applications in Optimal Control, exploring techniques, examples, optimality definitions, and necessary conditions.
Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.
Introduces dynamical systems, covering modeling, laws of motion, linearity, time invariance, and external forces.
