Lectures related to Master theorem (analysis of algorithms)

Covers techniques for solving recurrences and introduces the Master Theorem.

Covers the substitution method, Master Theorem, and recursion trees for efficient algorithm analysis.

Introduces Merge Sort, a divide-and-conquer algorithm for efficient array sorting, discussing correctness, runtime analysis, linear-time merging, and recurrence solving techniques.

Matrix Multiplication and Divide-and-Conquer Techniques

Discusses matrix multiplication using divide-and-conquer techniques and introduces Strassen's algorithm for improved efficiency.

Solving Recurrences

Covers sorting algorithms, divide-and-conquer analysis, solving recurrences through induction, complexities of floors and ceilings, and the Master method.

Solving Recurrences

Focuses on solving recurrences in divide-and-conquer algorithms using various techniques and examples.

Riemannian Trust Regions: Global Convergence

Discusses regularity conditions, trust regions, and global convergence in optimization.

Maximum Subarray Problem

Explores the Master method, the Maximum Subarray Problem, and optimal solution structures.

Recursion Trees and Matrix Multiplication

Covers recursion trees, the maximum subarray problem, and matrix multiplication approaches.

Matrix Multiplication: Divide-and-Conquer

Covers divide-and-conquer in matrix multiplication, recursion trees, the master method, maximum-subarray problem, and smart algorithm.

Riemannian Trust Regions framework

Introduces the Riemannian Trust Regions (RTR) framework, covering conjugate directions, Newton's method, and model improvement.

RTR practical aspects + tCG

Explores practical aspects of Riemannian trust-region optimization and introduces the truncated conjugate gradient method.

Exact Methods for Integer Optimization

Covers exact methods for integer optimization, emphasizing Branch and Bound techniques.

Trust region methods: Global convergence with minimal effort

Explores trust region methods for global convergence with minimal effort in optimization on manifolds.

Dynamic Programming: Rod Cutting and Matrix Chain Multiplication

Covers dynamic programming techniques for solving the rod cutting and matrix chain multiplication problems.

Dynamic Programming: Solving Sequential Problems Efficiently

Explores dynamic programming for efficient problem-solving, illustrated with binomial coefficients and Pascal's triangle.