Lectures related to Solving Recurrences

Merge Sort: Sorting Algorithm

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

Merge Sort: Divide and Conquer

Explores the Merge Sort algorithm, applying the Divide and Conquer approach to sorting arrays efficiently.

Sorting Algorithms: Selection and Insertion

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

Algorithmic Challenges: Solutions and Optimization

Explores algorithmic challenges, time complexity, optimization, recursion, and probability calculations.

Algorithms in Computer Science: Search and Sort Techniques

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

Merge Sort: Divide, Conquer, Combine

Explores Merge Sort, a sorting algorithm that divides, conquers, and combines arrays efficiently to achieve O(nlog n) time complexity.

Quick Sort: Divide-and-Conquer

Explores the Quick Sort algorithm, focusing on its divide-and-conquer approach and time complexity analysis.

Merge Sort: Divide-and-Conquer

Introduces Merge Sort, a divide-and-conquer algorithm for efficient array sorting, discussing correctness, runtime analysis, linear-time merging, and recurrence solving techniques.

Hashing and Quick Sort

Covers the efficient implementation of hash tables and the Quick Sort algorithm.

Complexity of Algorithms: Examples + Q&A

Explores examples of algorithm complexity, sorting, and polynomial computations.

Recursive Sorting: Merge Sort

Explains recursive sorting using Merge Sort and its linearithmic complexity.

Sorting Algorithms: Sorting Methods and Comparison

Explores sorting methods, insertion sort, and algorithm comparison for efficient data organization.

Introduction to Algorithms: Course Overview and Basics

Introduces the CS-250 Algorithms course, covering its structure, objectives, and key topics in algorithmic problem-solving.

Complexity of Algorithms

Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.

Complexity & Induction: Algorithms & Proofs

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

Computation & Algorithms II: Sorting and Recursive Algorithms

Explores sorting and recursive algorithms, including complexity analysis, maximal value, and binary search.

Matrix Multiplication and Divide-and-Conquer Techniques

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

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Derivatives, O-Notation

Explores derivatives, O-Notation, extrema, and algorithm complexity in Analysis 1.

Theory of Computation: Complexity of Problems

Explores the theory of computation, undecidable problems, complexity measurement, and the P complexity class.