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Convergence absolue

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Convergence absolue

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Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization

Implementation of Diverted Equilibria in the GBS simulation code

Dynamic Optimization of Constrained Semi-Batch Processes Using Pontryagin’s Minimum Principle – An Effective Quasi-Newton Approach

Asynchronous updates for stochastic gradient descent

Payoff-Based Approach to Learning Nash Equilibria in Convex Games * *This research is partially supported by M. Kamgarpour’s European Union ERC Starting Grant, CONENE.

Real-Time Optimization Based on Adaptation of Surrogate Models

Accurate, Stable and Efficient Modal Calculations of Photoelectrically Useful Absorption in Lamellar Metallic and Semiconductor Diffraction Gratings

Multi-index stochastic collocation convergence rates for random PDEs with parametric regularity

Dynamic Optimization of Constrained Semi-Batch Processes Using Pontryagin’s Minimum Principle – An Effective Quasi-Newton Approach

On aggregative and mean field games with applications to electricity markets

Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization

Accurate, Stable and Efficient Modal Calculations of Photoelectrically Useful Absorption in Lamellar Metallic and Semiconductor Diffraction Gratings

Implementation of Diverted Equilibria in the GBS simulation code

Dynamic Optimization of Constrained Semi-Batch Processes Using Pontryagin’s Minimum Principle – An Effective Quasi-Newton Approach

Asynchronous updates for stochastic gradient descent

Payoff-Based Approach to Learning Nash Equilibria in Convex Games * *This research is partially supported by M. Kamgarpour’s European Union ERC Starting Grant, CONENE.

Real-Time Optimization Based on Adaptation of Surrogate Models

Multi-index stochastic collocation convergence rates for random PDEs with parametric regularity

On aggregative and mean field games with applications to electricity markets

Dynamic Optimization of Constrained Semi-Batch Processes Using Pontryagin’s Minimum Principle – An Effective Quasi-Newton Approach