CQFD - 2014 - Annual activity report

CQFD

CQFD - 2014

Project-Team Cqfd

Members

Overall Objectives

Presentation

Research Program

Application Domains

Dependability and safety

New Software and Platforms

New Results

Highlights of the Year
Approximate Kalman–Bucy filter for continuous-time semi-Markov jump linear systems
Modeling and optimization of a launcher integration process
Numerical approximation for optimal stopping of MDP under partial observation
Classification of EEG signals by evolutionary algorithm
Probabilistic low-rank matrix completion with adaptive spectral regularization algorithms
Variable selection to construct indicators of quality of life for data structured in groups
Efficiency of simulation in monotone hyper-stable queueing networks
Control of parallel non-observable queues: asymptotic equivalence and optimality of periodic policies
The economics of the cloud: price competition and congestion
Generalized Nash Equilibria for Platform-as-a-Service Clouds
Stochastic approximations of constrained discounted Markov decision processes
Non-Parametric Estimation of the Conditional Distribution of the Interjumping Times for Piecewise-Deterministic Markov Processes
Approximation of average cost Markov decision processes using empirical distributions and concentration inequalities
Piecewise Deterministic Markov Processes based approach applied to an offshore oil production system
Optimal Trajectories for Underwater Vehicles by Quantization and Stochastic control
Multi-Objective Design and Maintenance Optimization of the Heated Hold-Up Tank Modeled by Piecewise Deterministic Markov Processes
Conditional quantile estimation through optimal quantization
Conditional quantile estimator based on optimal quantization: from theory to practice
QuantifQuantile : an R package for performing quantile regression trough optimal quantization
Transcriptome profile analysis reveals specific signatures of pollutants in Atlantic eels
Comparaison of kernel density estimators with assumption on number of modes : application on environmental monitoring data
A new sliced inverse regression method for multivariate response
An introduction to dimension reduction in nonparametric kernel regression
Hidden Markov Model for the detection of a degraded operating mode of optronic equipment
On the asymptotic behavior of the Nadaraya-Watson estimator associated with the recursive SIR method
Evolving Genetic Programming Classifiers with Novelty Search
Detecting mental states of alertness with genetic algorithm variable selection
A comparison of fitness-case sampling methods for Symbolic Regression
Geometric Semantic Genetic Programming with Local Search

Bilateral Contracts and Grants with Industry

Partnerships and Cooperations

Dissemination

Bibliography

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Section: Overall Objectives

Presentation

The core component of our scientific agenda focuses on the development of statistical and probabilistic methods for the modeling and the optimization of complex systems. These systems require mathematical representations which are in essence dynamic and stochastic with discrete and/or continuous variables. This increasing complexity poses genuine scientific challenges that can be addressed through complementary approaches and methodologies:

Modeling: design and analysis of realistic and tractable models for such complex real-life systems and various probabilistic phenomena;
Estimation: developing theoretical and computational procedures in order to estimate and evaluate the parameters and the performance of the system;
Optimization: developing theoretical and numerical control tools to optimize the performance of complex systems such as computer systems and communication networks.

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