Publications related to A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

Nonlinear interactions of ion acoustic waves explored using fast imaging decompositions

Fast camera imaging is used to study ion acoustic waves propagating azimuthally in a magnetized plasma column. The high-speed image sequences are analyzed using proper orthogonal decomposition and 2D Fourier transform, allowing to evaluate the assets and d ...

AIP Publishing2023

Learning to make mixed-integer robot motion planning easy

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Robot motion planning involves finding a feasible path for a robot to follow while satisfying a set of constraints and optimizing an objective function. This problem is critical for enabling robots to navigate and perform tasks in realworld environments. H ...

2023

Fast in vivo assay of creatine kinase activity in the human brain by P-31 magnetic resonance fingerprinting

Lijing Xin, Daniel Wenz, Mark Stephan Widmaier, Songi Lim

A new and efficient magnetisation transfer P-31 magnetic resonance fingerprinting (MT-P-31-MRF) approach is introduced to measure the creatine kinase metabolic rate kCK

{k}_{\mathrm{CK}}

between phosphocreatine (PCr) and adenosine triphosphate (ATP) i ...

WILEY2023

Linear Recursive State Estimation of Hybrid and Unbalanced AC/DC Micro-Grids using Synchronized Measurements

Mario Paolone, Willem Lambrichts

In this paper, we present an exact (i. e. non-approximated) and linear measurement model for hybrid AC/DC microgrids for recursive state estimation (SE). More specifically, an exact linear model of a voltage source converter (VSC) is proposed. It relies on ...

New York2023

PROBING INTRACELLULAR ELASTICITY WITH MINIMAL-HESSIAN REGISTRATION

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We propose an image-based elastography method to measure the heterogeneous stiffness inside a cell and its nucleus. It uses a widely accessible setup consisting of plate compression imaged with fluorescence microscopy. Our framework recovers a spatial map ...

New York2023

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

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In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

EPFL2023

Stochastic adaptive resampling for the estimation of discrete choice models

Michel Bierlaire, Nicola Marco Ortelli, Matthieu Marie Cochon de Lapparent

In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

2023

Hybridisation Scenarios of Solid Oxide Fuel Cells, Batteries, and Internal Combustion Engines for Waterborne Transportation

François Maréchal, Daniel Alexander Florez Orrego

The shipping industry was responsible for about 3% of global greenhouse gas (GHG) emissions in 2018. In this context, the International Maritime Organisation (IMO) has established stringent targets to reduce GHG emissions by at least 50% by 2050 compared t ...

Universidad de Las Palmas de Gran Canaria2023

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

Michel Bierlaire, Claudia Bongiovanni

In this paper, we formulate a mixed integer linear program (MILP) for the simulated maximum likelihood estimation (MLSE) problem and devise a Benders decomposition approach to speed up the solution process. This framework can be applied to any advanced dis ...

2022

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

Michel Bierlaire, Claudia Bongiovanni

In this paper, we formulate a mixed integer linear program (MILP) for the simulated maximum likelihood estimation (MLSE) problem and devise a Benders decomposition approach to speed up the solution process. This framework can be applied to any advanced dis ...

2022

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

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Nonlinear interactions of ion acoustic waves explored using fast imaging decompositions

Learning to make mixed-integer robot motion planning easy

Fast in vivo assay of creatine kinase activity in the human brain by P-31 magnetic resonance fingerprinting

Linear Recursive State Estimation of Hybrid and Unbalanced AC/DC Micro-Grids using Synchronized Measurements

PROBING INTRACELLULAR ELASTICITY WITH MINIMAL-HESSIAN REGISTRATION

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Stochastic adaptive resampling for the estimation of discrete choice models

Hybridisation Scenarios of Solid Oxide Fuel Cells, Batteries, and Internal Combustion Engines for Waterborne Transportation

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

Nonlinear interactions of ion acoustic waves explored using fast imaging decompositions

Fast in vivo assay of creatine kinase activity in the human brain by P-31 magnetic resonance fingerprinting

Linear Recursive State Estimation of Hybrid and Unbalanced AC/DC Micro-Grids using Synchronized Measurements

PROBING INTRACELLULAR ELASTICITY WITH MINIMAL-HESSIAN REGISTRATION

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Stochastic adaptive resampling for the estimation of discrete choice models

Hybridisation Scenarios of Solid Oxide Fuel Cells, Batteries, and Internal Combustion Engines for Waterborne Transportation

Learning to make mixed-integer robot motion planning easy

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models