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Concept

Explicit and implicit methods

Related publications (27)

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

Harsh Ambarishkumar Shukla

The research community has been making significant progress in hardware implementation, numerical computing and algorithm development for optimization-based control. However, there are two key challenges that still have to be overcome for optimization-base ...

EPFL2021

Nonlinear study on a rigid rotor supported by herringbone grooved gas bearings: Theory and validation

Jürg Alexander Schiffmann, Patrick Hubert Wagner, Philipp Kaspar Bättig, Wanhui Liu

The nonlinear behavior of a rigid rotor supported by herringbone grooved journal gas bearings (HGJBs) was investigated in this study. The two-dimensional narrow groove theory (2D-NGT) was adopted to model the HGJBs. A set of integrated rotor-bearing state ...

2021

Modeling Supply Chain Disruptions: A Network Flow Approach

René Yves Glogg

Globalization, outsourcing and cost optimization have all contributed to increased supply chain vulnerability, yet our understanding of effective mitigation strategies remains limited. In our research, we study the effects of disruptions on supply chain ne ...

EPFL2021

On the interplay effect for moving targets treated with the CyberKnife static tracking system

François Bochud, Yihan Jia

Purpose: To assess the interplay effect amplitude between different planned MU distributions and respiratory patterns in the CyberKnife system when treating moving targets with static tracking technique. Methods: Small-and Large-Respiratory Motions (SRM an ...

2021

Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach

Volkan Cevher, Shaul Nadav Hallak

This paper develops a methodology for regret minimization with stochastic first-order oracle feedback in online, constrained, non-smooth, non-convex problems. In this setting, the minimization of external regret is beyond reach for first-order methods, and ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Numerical methods for deterministic and stochastic differential equations with multiple scales and high contrasts

Giacomo Rosilho De Souza

Mathematical models involving multiple scales are essential for the description of physical systems. In particular, these models are important for the simulation of time-dependent phenomena, such as the heat flow, where the Laplacian contains mixed and ind ...

EPFL2020

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Martin Vetterli, Paul Hurley, Matthieu Martin Jean-André Simeoni, Adrien Georges Jean Besson

Finite rate of innovation (FRI) is a powerful reconstruction framework enabling the recovery of sparse Dirac streams from uniform low-pass filtered samples. An extension of this framework, called generalised FRI (genFRI), has been recently proposed for han ...

2020