Category
Computational complexity theory
Related lectures (542)
Algorithmes: introductionMOOC: Information, Calcul, Communication: Introduction à la pensée informatique
Covers the basics of algorithms, problem-solving, and efficient resolution methods.
Complexity of Algorithms: Growth of Functions
Analyzes the growth of functions to understand algorithm efficiency and uses Big-O notation for characterization.
Complexity Analysis of FGD Algorithm
Analyzes the complexity of the FGD algorithm in terms of computational and memory requirements.
Computation & Algorithms II: Sorting and Recursive Algorithms
Explores sorting and recursive algorithms, including complexity analysis, maximal value, and binary search.
State Space Models: Expressivity of Transformers
Covers state space models and the expressivity of transformers in sequence copying tasks.
Deutsch and Josza Problem
Covers the Deutsch and Josza problem in quantum computation, focusing on boolean functions and oracles.
Introduction to Algorithms
Introduces the importance of studying algorithms, presents a clever algorithm for calculating an arithmetic series, and discusses efficiency and correctness in algorithms.
Recursive Enumerability: Turing Machines and Undecidable Languages
Covers recursively enumerable languages, Turing machines, and the construction of undecidable languages.
Graphical Models: Representing Probabilistic Distributions
Covers graphical models for probabilistic distributions using graphs, nodes, and edges.
Algorithmic Complexity: Visualization and Analysis
Explores algorithmic complexity, visualization of functions, and algorithm efficiency analysis using Python.