Explores the coin change problem, comparing greedy and dynamic programming algorithms for optimal solutions.
Covers source coding, Kraft's inequality, mutual information, Huffman procedure, and properties of tropical sequences.
Covers optimization methods, focusing on gradient methods and line search techniques.
Explores degree of freedom analysis, redundancy, and data reconciliation in process modeling and optimization.
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Explores optimization techniques like Metropolis-Hastings and Simulated Annealing through Markov chains and stationary distributions.
