Nombre de documents

7

CV de José Henrique De Morais Goulart


Thèse1 document

  • José Henrique de Morais Goulart. Estimation of structured tensor models and recovery of low-rank tensors. Other. Université Côte d'Azur, 2016. English. <NNT : 2016AZUR4147>. <tel-01466776>

Communication dans un congrès3 documents

  • José Henrique De Morais Goulart, Gérard Favier. Iterative hard thresholding based algorithms for low-rank tensor recovery. 20th Conference of the International Linear Algebra Society (ILAS) - Symposium on Tensors for Signals and Systems, Jul 2016, Leuven, Belgium. 2016. <hal-01364008>
  • José Henrique De Morais Goulart, Gérard Favier. An iterative hard thresholding algorithm with improved convergence for low-rank tensor recovery. 2015 European Signal Processing Conference (EUSIPCO 2015), Aug 2015, Nice, France. Proceedings of the 23rd European Signal Processing Conference. <hal-01132367v2>
  • José Henrique De Morais Goulart, Maxime Boizard, Remy Boyer, Gérard Favier, Pierre Comon. Statistical efficiency of structured cpd estimation applied to Wiener-Hammerstein modeling. 23rd European Signal Processing Conference (EUSIPCO-2015), Aug 2015, Nice, France. 2015. <hal-01118725v2>

Article dans une revue2 documents

  • José Henrique De Morais Goulart, Maxime Boizard, Rémy Boyer, Gérard Favier, Pierre Comon. Tensor CP Decomposition with Structured Factor Matrices: Algorithms and Performance. IEEE Journal of Selected Topics in Signal Processing, IEEE, 2016, 10 (4), pp.757-769. <hal-01246855>
  • José Henrique De Morais Goulart, Gérard Favier. An algebraic solution for the Candecomp/PARAFAC decomposition with circulant factors. SIAM Journal on Matrix Analysis and Applications, Society for Industrial and Applied Mathematics, 2014, 35 (4), pp.1543-1562. <http://epubs.siam.org/doi/abs/10.1137/140955963>. <hal-00967263v2>

Pré-publication, Document de travail1 document

  • José Henrique De Morais Goulart, Gérard Favier. Low-rank tensor recovery using sequentially optimal modal projections in iterative hard thresholding (SeMPIHT). Submitted to the SIAM Journal on Scientific Computing (SISC). 2016. <hal-01387529>