Nombre de documents

28


Article dans une revue9 documents

  • Samuel Vaiter, Gabriel Peyré, Jalal M. Fadili. Model Consistency of Partly Smooth Regularizers. IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2018, 64 (3), pp.1725-1737. 〈10.1109/TIT.2017.2713822〉. 〈hal-01658847〉
  • Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon, Samuel Vaiter. CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration . SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2017, 10 (1), pp.243-284. 〈10.1137/16M1080318〉. 〈hal-01333295v3〉
  • Antonin Chambolle, Pauline Tan, Samuel Vaiter. Accelerated Alternating Descent Methods for Dykstra-like problems. Journal of Mathematical Imaging and Vision, Springer Verlag, 2017, 59 (3), pp.481-497. 〈10.1007/s10851-017-0724-6〉. 〈hal-01346532〉
  • Pierre C. Bellec, Joseph Salmon, Samuel Vaiter. A sharp oracle inequality for Graph-Slope. Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2017, 11 (2), pp.4851-4870. 〈10.1214/17-EJS1364〉. 〈hal-01544680〉
  • Samuel Vaiter, Charles-Alban Deledalle, Jalal M. Fadili, Gabriel Peyré, Charles Dossal. The degrees of freedom of partly smooth regularizers . Annals of the Institute of Statistical Mathematics, Springer Verlag, 2017, 69 (4), pp.791 - 832. 〈10.1007/s10463-016-0563-z〉. 〈hal-00981634v4〉
  • Samuel Vaiter, Mohammad Golbabaee, Jalal M. Fadili, Gabriel Peyré. Model Selection with Low Complexity Priors. Information and Inference, Oxford University Press (OUP), 2015, 52 p. 〈hal-00842603v3〉
  • Charles-Alban Deledalle, Samuel Vaiter, Jalal M. Fadili, Gabriel Peyré. Stein Unbiased GrAdient estimator of the Risk (SUGAR) for multiple parameter selection. SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2014, 7 (4), pp.2448-2487. 〈hal-00987295v2〉
  • Samuel Vaiter, Gabriel Peyré, Charles Dossal, Jalal M. Fadili. Robust Sparse Analysis Regularization. IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2013, 59 (4), pp.2001-2016. 〈10.1109/TIT.2012.2233859〉. 〈hal-00627452v5〉
  • Samuel Vaiter, Charles Deledalle, Gabriel Peyré, Charles Dossal, Jalal M. Fadili. Local Behavior of Sparse Analysis Regularization: Applications to Risk Estimation. Applied and Computational Harmonic Analysis, Elsevier, 2013, 35 (3), pp.433-451. 〈10.1016/j.acha.2012.11.006〉. 〈hal-00687751v2〉

Communication dans un congrès11 documents

  • Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon, Samuel Vaiter. Characterizing the maximum parameter of the total-variation denoising through the pseudo-inverse of the divergence. SPARS 2017 (Signal Processing with Adaptive Sparse Structured Representations), Jun 2017, Lisbon, Portugal. 2017, 〈http://spars2017.lx.it.pt/index.html〉. 〈hal-01412059〉
  • Jalal M. Fadili, Gabriel Peyré, Samuel Vaiter, Charles-Alban Deledalle, Joseph Salmon. Reconstruction Stable par Régularisation Décomposable Analyse. Colloque sur le Traitement du Signal et des Images (GRETSI'13), Sep 2013, Brest, France. pp.ID208, 2013. 〈hal-00927561〉
  • Samuel Vaiter, Gabriel Peyré, Jalal M. Fadili. Robust Polyhedral Regularization. International Conference on Sampling Theory and Applications (SampTA), 2013, Bremen, Germany. 〈hal-00816377〉
  • Jalal M. Fadili, Gabriel Peyré, Samuel Vaiter, Charles-Alban Deledalle, Joseph Salmon. Stable Recovery with Analysis Decomposable Priors. SPARS 2013, Jul 2013, Lausanne, Switzerland. 1 pp, 2013. 〈hal-00926727〉
  • Jalal M. Fadili, Gabriel Peyré, Samuel Vaiter, Charles-Alban Deledalle, Joseph Salmon. Stable Recovery with Analysis Decomposable Priors. Proc. SampTA'13, Jul 2013, Bremen, Germany. pp.113-116, 2013. 〈hal-00926732〉
  • Samuel Vaiter, Gabriel Peyré, Jalal M. Fadili. Robustesse au bruit des régularisations polyhédrales. 24th GRETSI Symposium on Signal and Image Processing, Sep 2013, Brest, France. pp.ID130, 2013. 〈hal-00927075〉
  • Samuel Vaiter, Gabriel Peyré, Jalal M. Fadili, Charles-Alban Deledalle, Charles Dossal. The degrees of freedom of the group Lasso for a general design. SPARS'13, Jul 2013, Lausanne, Switzerland. 1 page, 2013. 〈hal-00926929〉
  • Samuel Vaiter, Charles Deledalle, Gabriel Peyré, Jalal M. Fadili, Charles Dossal. The Degrees of Freedom of the Group Lasso. International Conference on Machine Learning Workshop (ICML), 2012, Edinburgh, United Kingdom. 〈hal-00695292〉
  • Charles Deledalle, Samuel Vaiter, Gabriel Peyré, Jalal M. Fadili, Charles Dossal. Unbiased Risk Estimation for Sparse Analysis Regularization. Proc. ICIP'12, Sep 2012, Orlando, United States. pp.3053-3056, 2012. 〈hal-00662718〉
  • Charles-Alban Deledalle, Samuel Vaiter, Gabriel Peyré, Jalal M. Fadili, Charles Dossal. Risk estimation for matrix recovery with spectral regularization. ICML'2012 workshop on Sparsity, Dictionaries and Projections in Machine Learning and Signal Processing, Jun 2012, Edinburgh, United Kingdom. 〈hal-00695326v3〉
  • Charles Deledalle, Samuel Vaiter, Gabriel Peyré, Jalal M. Fadili, Charles Dossal. Proximal Splitting Derivatives for Risk Estimation. NCMIP'12, Apr 2012, France. 386, pp.012003, 2012, 〈10.1088/1742-6596/386/1/012003〉. 〈hal-00670213〉

Chapitre d'ouvrage1 document

Pré-publication, Document de travail4 documents

  • Yann Traonmilin, Samuel Vaiter, Rémi Gribonval. Is the 1-norm the best convex sparse regularization?. 2018. 〈hal-01819219〉
  • Yann Traonmilin, Samuel Vaiter. Optimality of 1-norm regularization among weighted 1-norms for sparse recovery: a case study on how to find optimal regularizations. 2018. 〈hal-01720871v3〉
  • Abdessamad Barbara, Abderrahim Jourani, Samuel Vaiter. Maximal Solutions of Sparse Analysis Regularization. 2017. 〈hal-01467965〉
  • Samuel Vaiter, Charles Deledalle, Gabriel Peyré, Jalal M. Fadili, Charles Dossal. The degrees of freedom of the Group Lasso for a General Design. 2012. 〈hal-00768896v2〉

Rapport1 document

  • Samuel Vaiter, Gabriel Peyré, Jalal M. Fadili. Model Consistency of Partly Smooth Regularizers. [Research Report] CNRS. 2014. 〈hal-00987293v4〉

Thèse2 documents

  • Samuel Vaiter. Low Complexity Regularization of Inverse Problems. General Mathematics [math.GM]. Université Paris Dauphine - Paris IX, 2014. English. 〈NNT : 2014PA090055〉. 〈tel-01130672〉
  • Samuel Vaiter. Low Complexity Regularizations of Inverse Problems. Information Theory [math.IT]. Université Paris Dauphine - Paris IX, 2014. English. 〈tel-01026398〉