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Lecture

Computational Aspects of Optimization

Related lectures (33)

Heuristic Optimization Methods

Explores heuristic optimization methods to find the global optimum efficiently.

Optimising Neuron Models: eFEL and BluePyOpt

Introduces eFEL and BluePyOpt for optimizing neuron models with experimental data, using evolutionary algorithms.

Bio-Inspired Learning: Neural Networks, Genetic Algorithms

Explores bio-inspired learning with neural networks and genetic algorithms, covering structure, training, and practical applications.

Tools for Constraining Neuron Models MOOC: Simulation Neurocience

Covers tools for constraining neuron models using eFEL and BluePyOpt.

Optimization Methods: Theory Discussion

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

Deep Generative Models in Drug Discovery

Explores the application of deep generative models in drug discovery, focusing on designing small molecules and optimizing molecular structures.

Optimisation in Energy Systems

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

Optimization with Constraints: KKT Conditions

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Structures in Non-Convex Optimization

Covers non-convex optimization, deep learning training problems, stochastic gradient descent, adaptive methods, and neural network architectures.

Optimization Techniques: Local Search, VNS, Simulated Annealing

Explores optimization techniques like local search, VNS, and simulated annealing.

Optimization Methods

Covers unconstrained and constrained optimization, optimal control, neural networks, and global optimization methods.

High Performance OPF Solvers

Explores high-performance OPF solvers, addressing challenges in power system optimization and showcasing significant speed-ups and memory-efficient approaches.

Energy Systems Optimization

Explores energy systems modeling, optimization, and cost analysis for efficient operations.

Applications of GAMP

Delves into applying the GAMP algorithm to simplify the lasso problem and analyze optimization challenges in neural networks.

Energy optimization strategies

Covers brainstorming options for smart operation changes, heat recovery, and PV panel performance.

Optimization and Simulation

Explores optimization techniques like Metropolis-Hastings and Simulated Annealing through Markov chains and stationary distributions.

Multi-arm Bandits

Discusses algorithms for balancing exploration and exploitation in decision-making processes.

Optimization Methods in Machine Learning

Explores optimization methods in machine learning, emphasizing gradients, costs, and computational efforts for efficient model training.

In Silico Neuroscience: Ion Channels and Neuronal Models

Explores detailed modeling of ion channels and neuronal morphologies in in silico neuroscience, covering neuron classification, ion channel kinetics, and experimental observations.

Optimality of Convergence Rates: Accelerated/Stochastic Gradient Descent

Covers the optimality of convergence rates in accelerated and stochastic gradient descent methods for non-convex optimization problems.