Lectures related to Parameterized complexity

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.

Conclusions on Statistical Learning Theory

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

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.

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.

Graph Coloring: Random vs Symmetrical

Compares random and symmetrical graph coloring in terms of cluster colorability and equilibrium.

Optimization Algorithms

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

Algorithmic Complexity: Definition and Examples

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

Simon Problem 4: Quantum State and Complexity Analysis

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

Understanding Complexity: Algorithms and NP Problems

Covers complexity classes, tractable problems, the class NP, NP-complete problems, and summarizes the concept of tractable problems.

Understanding Complexity: Tractable Problems and NP-Complete

Covers complexity classes, effect on computer time, tractable problems, class NP, and NP-complete problems.

Linear Algebra Complexity

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

Complexity of Algorithms: Quiz + Answers

Covers the time complexity of algorithms and includes a quiz.

Dijkstra's Algorithm: All-Pairs

Covers Dijkstra's algorithm and its application to the all-pairs shortest path problem.

Implementation Research: Concepts and Scope

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

Improved Algorithm: Three-Color Parity Games

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

Elements of Computational Complexity

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

Dynamic Programming: Solving Sequential Problems Efficiently

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

Challenges in Bit-Precise Reasoning

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