Lectures related to Complexity of Algorithms: Advanced Big-O Facts

Explores recursion in programming, discussing its benefits, challenges, and impact on algorithm complexity.

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

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

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

Explores sorting and recursive algorithms, including complexity analysis, maximal value, and binary search.

Delves into the complexity of factoring polynomials and the implications for security.