An Inertial Parallel and Asynchronous Forward-Backward Iteration for Distributed Convex Optimization

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We enable the estimation of the per-axon axial diffusivity from single encoding, strongly diffusion-weighted, pulsed gradient spin echo data. Additionally, we improve the estimation of the per-axon radial diffusivity compared to estimates based on spherica ...

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We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge is thus to generate a sequence of feasible points converging towards an optim ...

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

An Inertial Parallel and Asynchronous Forward-Backward Iteration for Distributed Convex Optimization

Chattez avec Graph Search

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Harmonic Power-Flow Study of Hybrid AC/DC Grids with Converter-Interfaced Distributed Energy Resources

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Flexible High Power Electronics Solutions for Hydro-Power Applications

Axial and radial axonal diffusivities and radii from single encoding strongly diffusion-weighted MRI

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Homogenization results for the generator of multiscale Langevin dynamics in weighted Sobolev spaces

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