Lectures related to Algorithmes: introduction

Solving Parity Games in Practice

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

Complexity & Induction: Algorithms & Proofs

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

Graph Algorithms II: Traversal and Paths

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

Minimum Spanning Trees: Prim's Algorithm

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

Elements of computational complexity

Covers classical and quantum computational complexity concepts and implications.

Theory of Computability: Solvability and Complexity

Explores the theory of computability, decision problems, complexity classes, and the 'P vs. NP' conundrum.

Complexity Classes: Introduction and Examples

Introduces complexity classes, including P and NP, and explores examples of easy and hard problems.

Dynamic Programming: Knapsack

Explores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.

Communication Amid Uncertainty

Explores challenges in human communication, context importance, compression problems, uncertain functionality, and proof verification.

Graph Algorithms: Modeling and Traversal

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

Stein Algorithm: Polynomial Identity Testing

Explores the Stein algorithm for polynomial identity testing and the minimization of a cut problem.

Introduction to Information, Computation, and Communication

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

Fixed Points in Graph Theory

Focuses on fixed points in graph theory and their implications in algorithms and analysis.

Complexity & Induction: Algorithms & Proofs

Explores worst-case complexity, mathematical induction, and algorithms like binary search and insertion sort.

Promise Constraint Satisfaction and Width

Covers Promise Constraint Satisfaction Problems complexity, width, graph coloring, polymorphisms, and algorithms.

Algorithmic Complexity: Theta Notation

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

Causal Inference: Learning Graph Structures

Explores causal inference through learning graph structures for causal reasoning from observational data.

Dynamic Programming: Shortest Paths Algorithms

Explores dynamic programming strategies for finding shortest paths in networks with various algorithms and complexities.

Elements of Computational Complexity

Introduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.

Theory of Computation: Decidability and Complexity

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