Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.
Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.
Covers optimization algorithms, convergence properties, and time complexity of sequences and functions.
Introduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.
Delves into challenges of learning from probabilistic models, covering computational complexity, data reconstruction, and statistical gaps.
