Lectures related to Integer Optimization: Theory and Applications

Explores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.

Explores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.

Covers the concept of algorithms, loop invariants, and examples of algorithmic problem-solving.

Explores counterfactuals in SEMs and D-Separation in graphical models.