Algorithms: Final Exam Review

Related lectures (20)

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Explains two-phase construction for arrays, hash tables, and search trees in parallel.

Covers B+ Trees, a key data structure for efficient indexing in databases.

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

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

Explores optimal binary search trees to minimize expected search cost and discusses graphs representation using adjacency matrices and lists.

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

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

Covers search algorithms, focusing on abductive reasoning and heuristic search strategies.

Explores algorithm growth, search complexities, and logarithmic properties in depth, with practical exercises included.

Introduces recursion and binary search algorithms for efficient problem-solving.