Lectures related to Noncommutative Smith Form

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

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

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

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

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

Covers variance reduction techniques in optimization, focusing on gradient descent and stochastic gradient descent methods.

Explores abductive reasoning, search algorithms, and heuristic search for problem-solving.

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

Explores double descent curves and overparametrization in machine learning models, highlighting the risks and benefits.

Explores Replica Symmetry Breaking in the Random Energy Model, discussing configurational entropy and condensation.

Covers the basics of information theory, entropy, and fixed points in graph colorings and the Ising model.

Explores undecidability through recursive languages, Turing machines, and the halting problem.

Covers the computation of the picking factor and related exercises.

Covers basic algorithm ingredients, search algorithms, control structures, and algorithm correctness.

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

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

Analyzes the growth of functions to understand algorithm efficiency and uses Big-O notation for characterization.

Covers the theory of computability and the halting problem in algorithms.

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