Lecture

Solving Recurrences and Recursion Trees

Related lectures (16)

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

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

Matrix Multiplication and Divide-and-Conquer Techniques

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

Divide-and-Conquer: Merge Sort

Explores loop invariants, time analysis, and the Divide-and-Conquer approach with a focus on Merge Sort.

Merge Sort: Divide-and-Conquer

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

Problem-solving Strategies 2: Recursion

Explores problem-solving strategies like recursion and divide and conquer methods, with examples such as the Towers of Hanoi.

Algorithm Design: Divide and Conquer

Covers recursion, dynamic programming, and algorithm design using divide and conquer strategies.

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.

Problem Solving Strategies: General Overview

Presents methods for problem-solving, emphasizing 'Divide and Conquer', recursion, and dynamic programming.

Dynamic Programming: Rod Cutting and Matrix Chain Multiplication

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

Solving Parity Games in Practice

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Introduction to Algorithms

Introduces algorithms as problem-solving procedures, covering complexity, correctness, and implementation in various languages.

Algorithms: Final Exam Review

Provides a detailed review of the 2016 final exam, covering various algorithmic problems.

Matrix Multiplication and Heaps: Efficient Algorithms

Discusses Strassen's algorithm for matrix multiplication and heaps, covering efficient algorithms and their applications in computer science.

Recursive Functions: Substitution Interpreter

Covers the implementation of recursive functions using substitutions and environments, showcasing the ability to execute computable functions.