Ford-Fulkerson: a worked example

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Simplex Algorithm: Basics

Introduces the Simplex algorithm for solving flow problems and handling negative cost cycles.

Suspension Optimisation: Performance Analysis and Optimization

Explores the design and optimization of car suspensions for improved performance.

PCA: Derivation and Optimization

Covers the derivation of PCA projection, error minimization, and eigenvector optimization.

Quantum Approximate Optimization Algorithm

Covers the Quantum Approximate Optimization Algorithm, physically inspired unitary coupled cluster ansatz, hardware-efficient ansatz, and variational quantum eigensolver.

Monte Carlo Chain: Motivation and Algorithm

Explores the motivation and algorithm behind the Monte Carlo Chain method.

Coin Rendering: Part 1

Covers coin rendering and the limitations of the greedy algorithm in finding optimal solutions.

Optimization Methods: Theory Discussion

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Building Robust Ensembles via Margin Boosting

Delves into building robust ensembles through margin boosting for improved adversarial defense in machine learning models.

Variance Reduction: Strategies and Applications

Discusses variance reduction techniques in stochastic simulation, focusing on allocation strategies and replica generation algorithms.

Descent methods and line search: Finiteness of the line search algorithm

Explores the Wolfe conditions for line search algorithms and proves the finiteness of the line search parameter.