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6 papers · 1 filter
Discovering Knowledge using a Constraint-based Language
Patrice Boizumault, Bruno Crémilleux, Mehdi Khiari +2
Discovering pattern sets or global patterns is an attractive issue from the pattern mining community in order to provide useful information. By combining local patterns satisfying…
New Polynomial Classes for Logic-Based Abduction
B. Zanuttini
We address the problem of propositional logic-based abduction, i.e., the problem of searching for a best explanation for a given propositional observation according to a given prop…
Deconvolution under Poisson noise using exact data fidelity and synthesis or analysis sparsity priors
François-Xavier Dupé, Jalal Fadili, Jean-Luc Starck
In this paper, we propose a Bayesian MAP estimator for solving the deconvolution problems when the observations are corrupted by Poisson noise. Towards this goal, a proper data fid…
Data augmentation for galaxy density map reconstruction
François-Xavier Dupé, Jalal Fadili, Jean-Luc Starck
The matter density is an important knowledge for today cosmology as many phenomena are linked to matter fluctuations. However, this density is not directly available, but estimated…
Inverse Problems with Poisson noise: Primal and Primal-Dual Splitting
François-Xavier Dupé, Jalal Fadili, Jean-Luc Starck
In this paper, we propose two algorithms for solving linear inverse problems when the observations are corrupted by Poisson noise. A proper data fidelity term (log-likelihood) is i…
Linear inverse problems with noise: primal and primal-dual splitting
François-Xavier Dupé, Jalal Fadili, Jean-Luc Starck
In this paper, we propose two algorithms for solving linear inverse problems when the observations are corrupted by noise. A proper data fidelity term (log-likelihood) is introduce…