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Related lectures (22)

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

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Provides an overview of essential search and sort algorithms in computer science.

Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.

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

Covers hashing, sorting, extendible hashing, linear hashing, and external sorting.

Explains the merge sort algorithm, its correctness, and time complexity compared to other sorting algorithms.

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

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

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