Optimization

Convex optimization, evolutionary algorithms, and search methods for AI.

Convex Optimization

Convex functions, duality, interior-point methods, and convex problem formulations.

Evolutionary Algorithms

Genetic algorithms, evolution strategies, and nature-inspired optimization.

Simulated annealing, particle swarm, ant colony, and global search methods.

Combinatorial Optimization

TSP, scheduling, integer programming, and discrete optimization problems.

Bayesian Optimization

Gaussian processes, acquisition functions, and hyperparameter tuning.

Multi-Objective Optimization

Pareto fronts, trade-off analysis, and optimizing competing objectives.

Constrained Optimization

Lagrange multipliers, KKT conditions, and optimization with constraints.