Lectures related to Complexity of Algorithms: Big-O

Covers the complexity analyses of algorithms and their worst-case time complexities.

Analyzes the growth of functions to understand algorithm efficiency and uses Big-O notation for characterization.

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

Explores the analysis of the measurement process in the Shor Algorithm.

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Introduces an improved algorithm for three-color parity games, focusing on progress measures, acceleration, and practical speed-up.