Marc Schoenauer

research

∙ 09/11/2023

Interpretable learning of effective dynamics for multiscale systems

The modeling and simulation of high-dimensional multiscale systems is a ...

0 Emmanuel Menier, et al. ∙

research

∙ 06/18/2023

Meta-Learning for Airflow Simulations with Graph Neural Networks

The field of numerical simulation is of significant importance for the d...

0 Wenzhuo Liu, et al. ∙

research

∙ 04/28/2023

MultiZenoTravel: a Tunable Benchmark for Multi-Objective Planning with Known Pareto Front

Multi-objective AI planning suffers from a lack of benchmarks exhibiting...

0 Alexandre Quemy, et al. ∙

research

∙ 11/30/2022

Continuous Methods : Adaptively intrusive reduced order model closure

Reduced order modeling methods are often used as a mean to reduce simula...

0 Emmanuel Menier, et al. ∙

research

∙ 11/21/2022

DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations)

This paper proposes a novel Machine Learning-based approach to solve a P...

0 Matthieu Nastorg, et al. ∙

research

∙ 07/08/2022

Continuous Methods : Hamiltonian Domain Translation

This paper proposes a novel approach to domain translation. Leveraging e...

0 Emmanuel Menier, et al. ∙

research

∙ 02/22/2022

CD-ROM: Complementary Deep-Reduced Order Model

Model order reduction through the POD-Galerkin method can lead to dramat...

0 Emmanuel Menier, et al. ∙

research

∙ 11/05/2021

Frugal Machine Learning

Machine learning, already at the core of increasingly many systems and a...

10 Mikhail Evchenko, et al. ∙

research

∙ 05/17/2021

DISCO Verification: Division of Input Space into COnvex polytopes for neural network verification

The impressive results of modern neural networks partly come from their ...

0 Julien Girard-Satabin, et al. ∙

research

∙ 05/02/2021

Paradiseo: From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics —22 Years of Paradiseo—

The success of metaheuristic optimization methods has led to the develop...

0 Johann Dréo, et al. ∙

research

∙ 02/26/2021

Zoetrope Genetic Programming for Regression

The Zoetrope Genetic Programming (ZGP) algorithm is based on an original...

0 Aurélie Boisbunon, et al. ∙

research

∙ 11/25/2019

CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using Simulators

The topic of provable deep neural network robustness has raised consider...

4 Julien Girard-Satabin, et al. ∙

research

∙ 08/22/2019

LEAP nets for power grid perturbations

We propose a novel neural network embedding approach to model power tran...

2 Benjamin Donnot, et al. ∙

research

∙ 06/01/2019

Automated Machine Learning with Monte-Carlo Tree Search (Extended Version)

The AutoML task consists of selecting the proper algorithm in a machine ...

22 Herilalaina Rakotoarison, et al. ∙

research

∙ 03/21/2019

Multi-Domain Adversarial Learning

Multi-domain learning (MDL) aims at obtaining a model with minimal avera...

14 Alice Schoenauer-Sebag, et al. ∙

research

∙ 02/27/2019

On the Behaviour of Differential Evolution for Problems with Dynamic Linear Constraints

Evolutionary algorithms have been widely applied for solving dynamic con...

0 Maryam Hasani-Shoreh, et al. ∙

research

∙ 05/03/2018

Optimization of computational budget for power system risk assessment

We address the problem of maintaining high voltage power transmission ne...

0 Benjamin Donnot, et al. ∙

research

∙ 05/03/2018

Anticipating contingengies in power grids using fast neural net screening

We address the problem of maintaining high voltage power transmission ne...

0 Benjamin Donnot, et al. ∙

research

∙ 03/09/2018

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

Biological evolution provides a creative fount of complex and subtle ada...

0 Joel Lehman, et al. ∙

research

∙ 01/30/2018

Fast Power system security analysis with Guided Dropout

We propose a new method to efficiently compute load-flows (the steady-st...

0 Benjamin Donnot, et al. ∙

research

∙ 09/27/2017

Introducing machine learning for power system operation support

We address the problem of assisting human dispatchers in operating power...

0 Benjamin Donnot, et al. ∙

research

∙ 09/05/2017

Stochastic Gradient Descent: Going As Fast As Possible But Not Faster

When applied to training deep neural networks, stochastic gradient desce...

0 Alice Schoenauer-Sebag, et al. ∙

research

∙ 10/27/2016

Anomaly Detection with the Voronoi Diagram Evolutionary Algorithm

This paper presents the Voronoi diagram-based evolutionary algorithm (Vo...

0 Marti Luis, et al. ∙

research

∙ 06/19/2014

Racing Multi-Objective Selection Probabilities

In the context of Noisy Multi-Objective Optimization, dealing with uncer...

0 Gaétan Marceau, et al. ∙

research

∙ 06/10/2014

Maximum Likelihood-based Online Adaptation of Hyper-parameters in CMA-ES

The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is widely a...

0 Ilya Loshchilov, et al. ∙

research

∙ 09/16/2013

Computational Methods for Probabilistic Inference of Sector Congestion in Air Traffic Management

This article addresses the issue of computing the expected cost function...

0 Gaétan Marceau, et al. ∙

research

∙ 09/16/2013

Multiobjective Tactical Planning under Uncertainty for Air Traffic Flow and Capacity Management

We investigate a method to deal with congestion of sectors and delays in...

0 Gaétan Marceau, et al. ∙

research

∙ 09/16/2013

Strategic Planning in Air Traffic Control as a Multi-objective Stochastic Optimization Problem

With the objective of handling the airspace sector congestion subject to...

0 Gaétan Marceau, et al. ∙

research

∙ 08/12/2013

KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization

This paper investigates the control of an ML component within the Covari...

0 Ilya Loshchilov, et al. ∙

research

∙ 05/10/2013

Quality Measures of Parameter Tuning for Aggregated Multi-Objective Temporal Planning

Parameter tuning is recognized today as a crucial ingredient when tackli...

0 Mostepha Redouane Khouadjia, et al. ∙

research

∙ 05/06/2013

Multi-Objective AI Planning: Comparing Aggregation and Pareto Approaches

Most real-world Planning problems are multi-objective, trying to minimiz...

0 Mostepha Redouane Khouadjia, et al. ∙

research

∙ 04/10/2013

Sustainable Cooperative Coevolution with a Multi-Armed Bandit

This paper proposes a self-adaptation mechanism to manage the resources ...

0 François-Michel De Rainville, et al. ∙

research

∙ 12/20/2012

Multi-Objective AI Planning: Evaluating DAE-YAHSP on a Tunable Benchmark

All standard AI planners to-date can only handle a single objective, and...

0 Mostepha Redouane Khouadjia, et al. ∙

research

∙ 12/17/2012

Online Learning for Ground Trajectory Prediction

This paper presents a model based on an hybrid system to numerically sim...

0 Areski Hadjaz, et al. ∙

research

∙ 12/17/2012

Increasing Air Traffic: What is the Problem?

Nowadays, huge efforts are made to modernize the air traffic management ...

0 Areski Hadjaz, et al. ∙

research

∙ 07/01/2012

Alternative Restart Strategies for CMA-ES

This paper focuses on the restart strategy of CMA-ES on multi-modal func...

0 Ilya Loshchilov, et al. ∙

research

∙ 04/24/2012

Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on the BBOB-2012 noiseless testbed

In this paper, we study the performance of IPOP-saACM-ES and BIPOP-saACM...

0 Ilya Loshchilov, et al. ∙

research

∙ 04/24/2012

Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy testbed

In this paper, we study the performance of IPOP-saACM-ES, recently propo...

0 Ilya Loshchilov, et al. ∙

research

∙ 04/11/2012

Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy

This paper presents a novel mechanism to adapt surrogate-assisted popula...

0 Ilya Loshchilov, et al. ∙

research

∙ 05/17/2010

Evolving Genes to Balance a Pole

We discuss how to use a Genetic Regulatory Network as an evolutionary re...

0 Miguel Nicolau, et al. ∙

research

∙ 11/28/2006

On the Benefits of Inoculation, an Example in Train Scheduling

The local reconstruction of a railway schedule following a small perturb...

0 Yann Semet, et al. ∙

Marc Schoenauer

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