Lectures related to Big O notation

Covers proofs of Big-O using witnesses and rules to analyze algorithm complexity.

Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.

Explains Big-O notation for algorithm complexity analysis through polynomial examples and growth rate identification.

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

Covers the growth of functions and time complexity analysis for search algorithms.

Covers the review of significant figures and their importance in error estimation.

Explores Ruelle resonances for geodesic flows on non-compact manifolds, emphasizing the role of smoothness and eigenvalues in the dynamics.