Optimization algorithms

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Distributed Intelligent Systems: General Logistics and Course Overview

Covers the general logistics, course rationale, prerequisites, organization, credits, workload, grading, and course content, including swarm intelligence, foraging strategies, and collective phenomena.

Optimization on Manifolds: Context and Applications

Introduces optimization on manifolds, covering classical and modern techniques in the field.

Optimal Weak Transport Barycenters: Computational Aspects

By Elsa Cazelles explores the computation of optimal weak transport barycenters and their practical applications.

Proximal Gradient Descent: Optimization Techniques in Machine Learning

Discusses proximal gradient descent and its applications in optimizing machine learning algorithms.

Approximation Algorithms

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

Motor control systems

Explores motor control systems, covering algorithms, sensor integration, and practical applications in robotics and automation.

Primal-dual Optimization: Algorithms and Convergence

Explores primal-dual optimization algorithms for convex-concave minimax problems, discussing convergence properties and applications.

Greedy Algorithms & Matroids

Introduces greedy algorithms and matroids, highlighting their efficiency in solving optimization problems.

Optimisation in Energy Systems

Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.

Optimisation Strategies: Energy Systems Modelling and Optimization

Explores solving strategies for energy system optimization problems and different types of optimization approaches.