Concept

Divide-and-conquer algorithm

Related lectures (25)

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

Problem-solving Strategies 2: Recursion

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

Maximum Subarray Problem

Covers the Master method, maximum-subarray problem, and divide-and-conquer algorithmic paradigm.

Dataflow Analysis: Optimization

Explores dataflow analysis for optimization, including equations solving, live variables, reaching definitions, and very busy expressions.

Matrix Multiplication and Divide-and-Conquer Techniques

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

Recursive Algorithms: Divide and Conquer

Explores the concept of divide and conquer in recursive algorithms, exemplified by the Towers of Hanoi.

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.

Sampling from Rough Energy Landscapes

Explores challenges and strategies for sampling from rough energy landscapes, focusing on Monte Carlo integration and tuning algorithms.

Computation & Algorithms II: Sorting and Recursive Algorithms

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

Solving Recurrences: Master Method

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

Solving Recurrences and Recursion Trees

Covers techniques for solving recurrences and introduces the Master Theorem.

Sorting Algorithms: Selection and Insertion

Introduces selection and insertion sorting algorithms, explaining their correctness and time complexity.

Merge Sort: Divide and Conquer

Explores the Merge Sort algorithm, applying the Divide and Conquer approach to sorting arrays efficiently.

Non-Stochastic Control Problem: Online Gradient Boosting

Explores online gradient boosting for non-stochastic control problems, emphasizing policy regret minimization and stability in control.

Dynamic Programming: Fibonacci Numbers

Covers dynamic programming with a focus on Fibonacci numbers and the rod cutting problem.

Search and Routing Protocols

Explores unstructured and structured search and routing protocols, emphasizing the importance of network structure assumptions and introducing the 'Bubble Storm' algorithm.

Matrix Multiplication and Heaps: Efficient Algorithms

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

Solving Recurrences

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

Recursion and Karatsuba Multiplication

Explains recursion in algorithms and the Karatsuba multiplication method for large numbers.

Divide-and-Conquer: Merge Sort

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