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Lecture
Optimization Techniques: Local Search, VNS, Simulated Annealing
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Related lectures (32)
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Heuristic Optimization Methods
Explores heuristic optimization methods to find the global optimum efficiently.
Computational Aspects of Optimization
Explores optimization in neuron modeling, addressing underconstrained parameters, fitness functions, and successful fitting of firing patterns.
Algorithms & Growth of Functions
Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.
Search Algorithms: Abductive Reasoning
Explores abductive reasoning, search algorithms, and heuristic search for problem-solving.
Quasi-newton optimization
Covers gradient line search methods and optimization techniques with an emphasis on Wolfe conditions and positive definiteness.
Variance Reduction: Strategies and Applications
Discusses variance reduction techniques in stochastic simulation, focusing on allocation strategies and replica generation algorithms.
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.
Multi-arm Bandits
Discusses algorithms for balancing exploration and exploitation in decision-making processes.
Optimization algorithms
Covers optimization algorithms, focusing on Proximal Gradient Descent and its variations.
Optimization Methods
Covers the Newton's local method in Python using NumPy for optimization.
