Divide-and-Conquer: Merge Sort

Related lectures (24)

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Explores binary search, merge sort, recursion in algorithms, Fibonacci numbers, and dynamic programming.

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

Covers the analysis of algorithms, focusing on insertion sort and computational models.

Covers the concept of Merge Sort, a recursive sorting algorithm that divides a list into sublists until each sublist has one element.

Explores dynamic programming for palindromic subsequences, merging binary search trees, and finding the median of two sorted arrays.

Explores optimization problems and greedy algorithms for efficient decision-making.

Explores worst-case complexity, mathematical induction, and algorithms like binary search and insertion sort.

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

Covers the complexity analyses of algorithms and their worst-case time complexities.

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