Concept

Complexity class

Related lectures (30)

Algorithmic Complexity: Travel Time Analysis

Covers algorithmic complexity and travel time analysis, focusing on measuring the time taken by algorithms and evaluating their performance.

Elements of computational complexity

Covers classical and quantum computational complexity concepts and implications.

Linear Systems: Convergence and Methods

Explores linear systems, convergence, and solving methods with a focus on CPU time and memory requirements.

Solving Parity Games in Practice

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

Optimization Algorithms

Covers optimization algorithms, convergence properties, and time complexity of sequences and functions.

Transition to Smart Cities: Complexity and Interdependencies

Delves into the complexity and interdependencies of transitioning to smart cities, emphasizing the importance of a holistic approach.

Complex Systems: Critical Phenomena

Explores critical phenomena in complex systems, including stochastic objects, percolation, and combinatorial optimization.

Conclusions on Statistical Learning Theory

Explores conclusions from statistical learning theory, emphasizing function complexity, generalization, and the bias-variance trade-off.

Linear Programming: Optimization and Constraints

Explores linear programming optimization with constraints, Dijkstra's algorithm, and LP formulations for finding feasible solutions.

Challenges in Bit-Precise Reasoning

Covers challenges in bit-precise reasoning, including SMT-COMP results, AIG, bit-blasting, Tseitin transformation, and complexity classes.

Improved Algorithm: Three-Color Parity Games

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

Implementation Research: Concepts and Scope

Explores Implementation Research, addressing challenges in implementing health interventions and developing effective strategies for infectious diseases of poverty.

Algorithmic Complexity: Definition and Examples

Explores algorithm correctness, worst-case complexity analysis, and efficiency comparison based on input size.

Dynamic Programming: Solving Sequential Problems Efficiently

Explores dynamic programming for efficient problem-solving, illustrated with binomial coefficients and Pascal's triangle.

Generalization in Deep Learning

Explores generalization in deep learning, covering model complexity, implicit bias, and the double descent phenomenon.

Complexity Classes: Introduction and Examples

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

Simon Problem 4: Quantum State and Complexity Analysis

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

Linear Algebra Complexity

Explores the complexity of linear algebra operations and optimization methods, including Gaussian elimination and the simplex method.

Theory of Computability: Solvability and Complexity

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

Complexity of Algorithms: Big-O Notation

Explores algorithm complexity, big-O notation, induction, recursion, and analysis of running times, covering NP problems and complexity classes.