Project
Team
Cqfd
Overall Objectives
Scientific Foundations
Application Domains
New Results
- On the Existence of Strict Optimal Controls for Constrained, Controlled Markov Processes in Continuous-Time
- Approximation of Markov Decision Processes with General State Space
- Asymmetry tests for Bifurcating Auto-Regressive Processes with missing data
- Statistical study of asymmetry in cell lineage data
- Estimation of the jump rate of a PDMP
- Detection of a damaged operating mode of optronic equipment using Hidden Markov Model
- Optimal quantization applied to Sliced Inverse Regression
- Multivariate Analysis for the detection of the effect of a treatment
- Numerical computation of expectations of PDMP's
- Optimal stopping under partial observation
- Efficient simulation of the availability of a feedwater control system
- Othogonal Rotation in PCAMIX
- An adaptive SIR method for block-wise evolving data streams
- Classification of EEG data by evolutionary algorithm for the study of vigilance states
- Comparison of Kernel Density Estimators on Environmental Data with Assumption on Number of Modes
Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
Project
Team
Cqfd
Overall Objectives
Scientific Foundations
Application Domains
New Results
- On the Existence of Strict Optimal Controls for Constrained, Controlled Markov Processes in Continuous-Time
- Approximation of Markov Decision Processes with General State Space
- Asymmetry tests for Bifurcating Auto-Regressive Processes with missing data
- Statistical study of asymmetry in cell lineage data
- Estimation of the jump rate of a PDMP
- Detection of a damaged operating mode of optronic equipment using Hidden Markov Model
- Optimal quantization applied to Sliced Inverse Regression
- Multivariate Analysis for the detection of the effect of a treatment
- Numerical computation of expectations of PDMP's
- Optimal stopping under partial observation
- Efficient simulation of the availability of a feedwater control system
- Othogonal Rotation in PCAMIX
- An adaptive SIR method for block-wise evolving data streams
- Classification of EEG data by evolutionary algorithm for the study of vigilance states
- Comparison of Kernel Density Estimators on Environmental Data with Assumption on Number of Modes
Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
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