Lectures related to Girvan-Newman Algorithm

Theory of Computation: Decidability and Complexity

Delves into the theory of computation, covering decidability, complexity, P vs. NP, and reductions.

Complexity & Induction: Algorithms & Proofs

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

Introduction to Information, Computation, and Communication

Introduces the fundamental principles of Information, Computation, and Communication theory, covering genomics, medical imaging, and assistive technology.

Theory of Computation: NP Problems Examples

Examines NP problems, graph coloring, path optimization, and computational complexity distinctions in P and NP classes.

Solving Parity Games in Practice

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

Computation & Algorithms I

Covers the basics of algorithms, their historical significance, pseudo-code representation, and practical tasks in computational thinking.

Improved Algorithm: Three-Color Parity Games

Introduces an improved algorithm for three-color parity games, focusing on progress measures, acceleration, and practical speed-up.

Elements of computational complexity

Covers classical and quantum computational complexity concepts and implications.

Recursive Enumerability: Turing Machines and Undecidable Languages

Covers recursively enumerable languages, Turing machines, and the construction of undecidable languages.

Noncommutative Smith Form

Covers the computation of the Smith Form for noncommutative systems.

Distinct Elements: Count and Hash Functions

Covers counting distinct elements using hash functions and the median trick.

Algorithms & Growth of Functions

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

Linear Algebra: Efficiency and Complexity

Explores constraints, efficiency, and complexity in linear algebra, emphasizing convexity and worst-case complexity in algorithm analysis.

Dijkstra's Algorithm: All-Pairs

Covers Dijkstra's algorithm and its application to the all-pairs shortest path problem.

Dynamic Programming: Pascal's Triangle & Floyd's Algorithm

Explores dynamic programming through Pascal's Triangle and Floyd's Algorithm.

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Scripts and Algorithms: MATLAB and Octave Basics

Introduces the basics of scripts and algorithms using MATLAB and Octave for beginners.

Theory of Computation: Problems Definition and Counting (Denumerability)

Explores the theory of computation, emphasizing problems definition, counting, and the limits of algorithmic computation.

Algorithmic Complexity: Theta Notation

Explores algorithmic complexity, comparing growth rates using Theta notation and characterizing different complexity classes.

Simon Problem 4: Quantum State and Complexity Analysis

Explores the Simon Problem 4, analyzing quantum states and algorithm complexity.