Lectures related to Algorithms: Final Exam Review

Graph Algorithms II: Traversal and Paths

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

Covers graph properties, representations, and traversal algorithms using BFS and DFS.

Offers a recap before the Algorithms exam, covering problem-solving strategies and algorithm implementation with sample problems.

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.

Introduction to Algorithms: Basics and Importance

Covers the basics of algorithms, the importance of studying them, data structures, and the impact of algorithms on various fields.

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.

Algorithms in Computer Science: Search and Sort Techniques

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

Data Structures: Stacks, Queues, Linked Lists

Covers stacks, queues, linked lists, and binary search trees in data structures.

Optimal Binary Search Trees

Explains Optimal Binary Search Trees using dynamic programming and covers a midterm exam from 2016.

Minimum Spanning Trees: Prim's Algorithm

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.

Two-Phase Construction: Arrays & Hash Tables

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

Tree-Structured Indexing: B+ Trees Explained

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

Dynamic Programming: Palindromic Subsequences

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

Solving Parity Games in Practice

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

Optimal Binary Search Tree

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

Graph Algorithms: Modeling and Traversal

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

Complexity & Induction: Algorithms & Proofs

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

Search Algorithms: Abductive Reasoning

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

Algorithm Analysis: Growth, Search, and Logarithm

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

Recursion and Binary Search

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