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Algorithms Exam Preparation
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Related lectures (24)
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Algorithms: Final Exam Review
Provides a detailed review of the 2016 final exam, covering various algorithmic problems.
Complexity & Induction: Algorithms & Proofs
Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.
Recursion and Binary Search
Introduces recursion and binary search algorithms for efficient problem-solving.
Data Structures: Stacks, Queues, Linked Lists
Covers stacks, queues, linked lists, and binary search trees in data structures.
Dynamic Programming: Palindromic Subsequences
Explores dynamic programming for palindromic subsequences, merging binary search trees, and finding the median of two sorted arrays.
Binary Search Trees: Implementation and Operations
Covers the implementation and operations of basic data structures like stacks, queues, and linked lists, and introduces binary search trees.
Optimal Binary Search Trees
Explains Optimal Binary Search Trees using dynamic programming and covers a midterm exam from 2016.
Algorithmic Paradigms for Dynamic Graph Problems
Covers algorithmic paradigms for dynamic graph problems, including dynamic connectivity, expander decomposition, and local clustering, breaking barriers in k-vertex connectivity problems.
Optimal Binary Search Tree
Explores optimal binary search trees to minimize expected search cost efficiently.
Algorithm Analysis: Growth, Search, and Logarithm
Explores algorithm growth, search complexities, and logarithmic properties in depth, with practical exercises included.