Lectures related to Subset Sum: LLL Algorithm

Complexity & Induction: Algorithms & Proofs

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

Covers classical and quantum computational complexity concepts and implications.

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

Algorithmic Complexity: Theta Notation

Explores algorithmic complexity, comparing growth rates using Theta notation and characterizing different complexity classes.

Integer Factorization: Methods and Algorithms

Explores methods and algorithms for integer factorization, including testing for B smoothness and computing small primes.

Complexity of Algorithms: Proofs of Time Complexity

Covers the analysis of worst time complexity for algorithms and time complexity with real numbers and integers.

Shor's factoring algorithm: Quantum Phase Estimation

Covers Shor's factoring algorithm and the link between order finding and factoring.

Euclidean Algorithm: GCD Calculation

Covers the Euclidean algorithm for GCD calculation and algorithmic complexity analysis.

Complexity & Induction: Algorithms & Proofs

Explores worst-case complexity, mathematical induction, and algorithms like binary search and insertion sort.

Groups and Numbers: Hidden Subgroup Problem

Explores groups and numbers, emphasizing the hidden subgroup problem and its complexities in classic and quantum algorithms.

Complexity of Algorithms

Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.

Simon Problem 4: Quantum State and Complexity Analysis

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

Dynamic Programming: Rod Cutting and Matrix Chain Multiplication

Covers dynamic programming techniques for solving the rod cutting and matrix chain multiplication problems.

Subquadratic Attention Mechanisms: State Space Models Overview

Covers subquadratic attention mechanisms and state space models, focusing on their theoretical foundations and practical implementations in machine learning.

Improved Algorithm: Three-Color Parity Games

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

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Algorithmic Complexity: Travel Time Analysis

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

Numerical Methods: Runge-Kutta Approximation

Covers the Runge-Kutta method for approximating solutions of differential equations.

Factoring Polynomials: Complexity and Algorithms

Delves into the complexity of factoring polynomials and the implications for security.

Elements of Computational Complexity

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