Lecture
Theory of Computation: Counting and Decision Problems
Related lectures (21)
Theory of Computation: Problems Definition and Counting (Denumerability)
Explores the theory of computation, emphasizing problems definition, counting, and the limits of algorithmic computation.
Relations, Sequences and Summations
Covers strings, countable sets, cardinality, and the concept of countability, exploring the countability of various sets and Cantor diagonalization.
Cartesian Product and Induction
Introduces Cartesian product and induction for proofs using integers and sets.
Relations in Computer Science
Explores the properties of relations in computer science, including equivalence relations and the partition of a set.
Algorithms & Growth of Functions
Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.
Complexity & Induction: Algorithms & Proofs
Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.
Complexity & Induction: Algorithms & Proofs
Explores worst-case complexity, mathematical induction, and algorithms like binary search and insertion sort.
Sets and Operations: Introduction to Mathematics
Covers the basics of sets and operations in mathematics, from set properties to advanced operations.
Proofs and Logic: Introduction
Introduces logic, proofs, sets, functions, and algorithms in mathematics and computer science.
Nonlinear Dynamics: Chaos and Complex Systems
Explores countable and uncountable sets, Cantor set, Mandelbrot set, and Box dimension in nonlinear dynamics and complex systems.