Publications associées à Optimisation par essaims particulaires

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Convergence of adaptive algorithms for constrained weakly convex optimization

Volkan Cevher, Ahmet Alacaoglu, Yurii Malitskyi

We analyze the adaptive first order algorithm AMSGrad, for solving a constrained stochastic optimization problem with a weakly convex objective. We prove the

\tilde O(t^{-1/2})

rate of convergence for the squared norm of the gradient of Moreau envelope, ...

2021

Optimisation par essaims particulaires

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Cellulan World: Interactive Platform to Learn Swarm Behaviors

UNDERGRAD: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Finding symmetry breaking order parameters with Euclidean neural networks

Systematic Method for the Energy-Saving Potential Calculation of Air Conditioning Systems via Data Mining. Part II: A Detailed Case Study

Multikernel Regression with Sparsity Constraint

Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms

Convergence of adaptive algorithms for constrained weakly convex optimization

Data-Driven Convergence Prediction of Astrobots Swarms

Pareto-like sequential sampling heuristic for global optimisation

UNDERGRAD: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees

Data-Driven Convergence Prediction of Astrobots Swarms

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Systematic Method for the Energy-Saving Potential Calculation of Air Conditioning Systems via Data Mining. Part II: A Detailed Case Study

Cellulan World: Interactive Platform to Learn Swarm Behaviors

Pareto-like sequential sampling heuristic for global optimisation

Finding symmetry breaking order parameters with Euclidean neural networks

Multikernel Regression with Sparsity Constraint

Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms

Convergence of adaptive algorithms for constrained weakly convex optimization