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====== Practical uncertainty representations ====== | ====== Practical uncertainty representations ====== | ||
- | Work (mainly) benefiting from collaborations and discussions with D. Dubois, M. Troffaes, E. Miranda, L. Utkin, E. Chojancki and E. Quaeghebeur | + | Work (mainly) benefiting from collaborations and discussions with D. Dubois, M. Troffaes, E. Miranda, L. Utkin, E. Chojnacki, |
There exist many practical representations in imprecise probability theories, including possibility distributions, | There exist many practical representations in imprecise probability theories, including possibility distributions, | ||
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Our current focus in this area concerns the characterization of inconsistency and reliability degrees resulting either from assumptions about the source of information or from the combination of the different pieces of information. Such degrees can then be used to guide the fusion process. | Our current focus in this area concerns the characterization of inconsistency and reliability degrees resulting either from assumptions about the source of information or from the combination of the different pieces of information. Such degrees can then be used to guide the fusion process. | ||
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====== Uncertainty propagation and (in)dependence modelling ====== | ====== Uncertainty propagation and (in)dependence modelling ====== | ||
- | Work (mainly) benefiting from collaborations and discussions with D. Dubois, G. De Cooman E. Chojnacki, J. Baccou, T. Burger, M. Sallak | + | Work (mainly) benefiting from collaborations and discussions with D. Dubois, G. De Cooman, E. Chojnacki, J. Baccou, T. Burger, M. Sallak, M.C.M. Troffaes, F. Coolen, S. Ferson, |
How to propagate uncertainty analysis in various models is an important issue that may face several difficulties. Most of my research in this domain has concerned the propagation of uncertainty model through deterministic functions with methods combining Monte-Carlo simulation and interval analysis, with an industrial risk-assessment purpose. | How to propagate uncertainty analysis in various models is an important issue that may face several difficulties. Most of my research in this domain has concerned the propagation of uncertainty model through deterministic functions with methods combining Monte-Carlo simulation and interval analysis, with an industrial risk-assessment purpose. | ||
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Related problems are how to model independence to obtain tractable joint models (and how to compute with such latter models), or how to simulate a given imprecise probabilistic model. | Related problems are how to model independence to obtain tractable joint models (and how to compute with such latter models), or how to simulate a given imprecise probabilistic model. | ||
- | Some of our recent research also deals with the problem of how to efficiently evaluate the reliability when the component | + | Some of our recent research also deals with the problem of how to efficiently evaluate the reliability when the component |
====== Learning problems ====== | ====== Learning problems ====== | ||
- | Work (mainly) benefiting from collaborations and discussions with B. Quost, T. Denoeux, B. Ben Yaghlane, N. Sutton-Charani, | + | Work (mainly) benefiting from collaborations and discussions with B. Quost, T. Denoeux, B. Ben Yaghlane, N. Sutton-Charani, G. Yang, M. Masson, E. Hüllermeier, |
Outside of extending some classical classifiers (k-NN methods, Naïve networks) to imprecise probabilistic settings, our work currently focuses on the combination of classifiers, | Outside of extending some classical classifiers (k-NN methods, Naïve networks) to imprecise probabilistic settings, our work currently focuses on the combination of classifiers, | ||
- | One of our current favorite field of investigation is the so-called binary decomposition, | + | One of our current favorite field of investigation is the so-called binary decomposition, |
====== Applications ====== | ====== Applications ====== | ||
- | Work (mainly) benefiting from collaborations and discussions with P. Buche, B. Charnomordic, | + | Work (mainly) benefiting from collaborations and discussions with P. Buche, B. Charnomordic, |
We have applied ideas coming from imprecise probability theories and more generally concerning uncertainty handling to a number of frameworks, including: | We have applied ideas coming from imprecise probability theories and more generally concerning uncertainty handling to a number of frameworks, including: | ||
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* Flexible querying in data bases (P. Buche, V. Guillard) | * Flexible querying in data bases (P. Buche, V. Guillard) | ||
- | * Signal filtering with kernels (O. Strauss) | + | * Signal filtering with kernels (O. Strauss, F. Comby) |
* Knowledge Engineering (B. Charnomordic, | * Knowledge Engineering (B. Charnomordic, | ||
* Risk analysis and robust design (E. Chojancki, V. Guillard, M. Sallak) | * Risk analysis and robust design (E. Chojancki, V. Guillard, M. Sallak) | ||
+ | * Process modelling (C. Baudrit) | ||
+ | * Virtual training (I. Thouvenin) |