Remy Boyer
Professeur des universités
CNU : SECTION 61 - GENIE INFORMATIQUE, AUTOMATIQUE ET TRAITEMENT DU SIGNAL
Laboratoire / équipe
Publications
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"citationFull_s":"Maxence Giraud, Vincent Itier, Remy Boyer, Yassine Zniyed, André de Almeida. Tucker Decomposition Based on a Tensor Train of Coupled and Constrained CP Cores. 2023. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-04112156v1\">⟨hal-04112156⟩</a>",
"title_s":["Tucker Decomposition Based on a Tensor Train of Coupled and Constrained CP Cores"],
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"title_s":["Semi-Blind Joint Channel and Symbol Estimation for IRS-Assisted MIMO Systems"],
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"citationFull_s":"Abdelhak Boudehane, Laurent Albera, Arthur Tenenhaus, Laurent Le Brusquet, Remy Boyer. Parallelization Scheme for Canonical Polyadic Decomposition of Large-Scale High-Order Tensors. <i>Signal Processing</i>, 2022, 199, pp.108610. <a target=\"_blank\" href=\"https://dx.doi.org/10.1016/j.sigpro.2022.108610\">⟨10.1016/j.sigpro.2022.108610⟩</a>. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-03613806v1\">⟨hal-03613806⟩</a>",
"title_s":["Parallelization Scheme for Canonical Polyadic Decomposition of Large-Scale High-Order Tensors"],
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"title_s":["Schéma parallélisé-randomisé de la décomposition canonique polyadique pour la localisation de sources de courant intracérébral"],
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"citationFull_s":"Ouafae Karmouda, Boulanger Jeremie, Remy Boyer. Apprentissage supervisé à noyau basé sur la décomposition Canonique Polyadique (CP). <i>Gretsi 2022</i>, Sep 2022, Nancy, France. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-03685314v1\">⟨hal-03685314⟩</a>",
"title_s":["Apprentissage supervisé à noyau basé sur la décomposition Canonique Polyadique (CP)"],
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"citationFull_s":"Karmouda Ouafae, Remy Boyer, Boulanger Jeremie. High-Dimensional Data Learning Based on Tensorial-Singular Space of Tensor Train Cores. <i>EUSIPCO</i>, Aug 2022, Belgrade, Serbia. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-03672088v1\">⟨hal-03672088⟩</a>",
"title_s":["High-Dimensional Data Learning Based on Tensorial-Singular Space of Tensor Train Cores"],
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"citationFull_s":"Clémence Prévost, Pierre Chainais, Remy Boyer. FAST FUSION OF HYPERSPECTRAL AND MULTISPECTRAL IMAGES : A TUCKER APPROXIMATION APPROACH. 2022. <a target=\"_blank\" href=\"https://hal.science/hal-03617759v1\">⟨hal-03617759⟩</a>",
"title_s":["FAST FUSION OF HYPERSPECTRAL AND MULTISPECTRAL IMAGES : A TUCKER APPROXIMATION APPROACH"],
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"citationFull_s":"Yassine Zniyed, Sebastian Miron, Remy Boyer, David Brie. Fragility Margin of PWA Control Laws using A Hyperplane Based Binary Search Tree. <i>IFAC-PapersOnLine</i>, 2022, 55 (40), pp.2340-2345. <a target=\"_blank\" href=\"https://dx.doi.org/10.1109/CAMSAP45676.2019.9022651\">⟨10.1109/CAMSAP45676.2019.9022651⟩</a>. <a target=\"_blank\" href=\"https://centralesupelec.hal.science/hal-04494050v1\">⟨hal-04494050⟩</a>",
"title_s":["Fragility Margin of PWA Control Laws using A Hyperplane Based Binary Search Tree"],
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"citationFull_s":"Ouafae Karmouda, Jérémie Boulanger, Remy Boyer. Joint Factors And Rank Estimation For The Canonical Polyadic Decomposition Based On Convex Optimization. <i>IEEE Access</i>, 2022, 10, pp.82295-82304. <a target=\"_blank\" href=\"https://dx.doi.org/10.1109/ACCESS.2022.3189793\">⟨10.1109/ACCESS.2022.3189793⟩</a>. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-03717054v1\">⟨hal-03717054⟩</a>",
"title_s":["Joint Factors And Rank Estimation For The Canonical Polyadic Decomposition Based On Convex Optimization"],
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"citationFull_s":"Ouafae Karmouda, Jérémie Boulanger, Remy Boyer. SPEEDING UP OF KERNEL-BASED LEARNING FOR HIGH-ORDER TENSORS. <i>2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>, Jun 2021, Toronto (virtual), Canada. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-03126008v1\">⟨hal-03126008⟩</a>",
"title_s":["SPEEDING UP OF KERNEL-BASED LEARNING FOR HIGH-ORDER TENSORS"],
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"citationFull_s":"Ouafae Karmouda, Boulanger Jérémie, Remy Boyer. APPRENTISSAGE SUPERVISÉ RAPIDE POUR DES DONNÉES TENSORIELLES. <i>2eme Conférence Internationale Francophone sur la Science des Données</i>, Jun 2021, Marseille, France. <a target=\"_blank\" href=\"https://hal.science/hal-03257968v1\">⟨hal-03257968⟩</a>",
"title_s":["APPRENTISSAGE SUPERVISÉ RAPIDE POUR DES DONNÉES TENSORIELLES"],
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"citationFull_s":"Gilderlan T de Araújo, André L F de Almeida, Remy Boyer. Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Systems: A Tensor Modeling Approach. <i>IEEE Journal of Selected Topics in Signal Processing</i>, 2021, 15 (3), pp.789-802. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-03146480v1\">⟨hal-03146480⟩</a>",
"title_s":["Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Systems: A Tensor Modeling Approach"],
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"title_s":["Semi-blind joint symbols and multipath parameters estimation of MIMO systems using KRST/MKRSM coding"],
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"citationFull_s":"Le Trung Thanh, Karim Abed-Meraim, Nguyen Linh-Trung, Remy Boyer. Adaptive Algorithms for Tracking Tensor-Train Decomposition of Streaming Tensors. <i>European Signal Processing Conference (EUSIPCO'20)</i>, Jan 2021, Amsterdam, Netherlands. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-02865257v1\">⟨hal-02865257⟩</a>",
"title_s":["Adaptive Algorithms for Tracking Tensor-Train Decomposition of Streaming Tensors"],
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"citationFull_s":"Sebastian Miron, Yassine Zniyed, Remy Boyer, André L F de Almeida, Gérard Favier, et al.. Tensor methods for multisensor signal processing. <i>IET Signal Processing</i>, 2021, 14 (10), pp.693-709. <a target=\"_blank\" href=\"https://dx.doi.org/10.1049/iet-spr.2020.0373\">⟨10.1049/iet-spr.2020.0373⟩</a>. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-03024673v1\">⟨hal-03024673⟩</a>",
"title_s":["Tensor methods for multisensor signal processing"],
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"citationRef_s":"Yipeng Liu. <i>Tensors for Data Processing</i>, Chapter 15, Elsevier, 2021, Tensors for Data Processing",
"citationFull_s":"Yassine Zniyed, Ouafae Karmouda, Jérémie Boulanger, Remy Boyer, André L. F. de Almeida, et al.. Structured Tensor-Train Decomposition for Speeding-Up Kernel-Based Learning. Yipeng Liu. <i>Tensors for Data Processing</i>, Chapter 15, Elsevier, 2021, Tensors for Data Processing. <a target=\"_blank\" href=\"https://hal.univ-lille.fr/hal-03264296v1\">⟨hal-03264296⟩</a>",
"title_s":["Structured Tensor-Train Decomposition for Speeding-Up Kernel-Based Learning"],
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"title_s":["Tensor Train Representation of MIMO Channels using the JIRAFE Method"],
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"title_s":["High-order tensor estimation via trains of coupled third-order CP and Tucker decompositions"],
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"citationFull_s":"Martin Brossard, Virginie Ollier, Mohammed Nabil El Korso, Remy Boyer, Pascal Larzabal. [Technical Report] Multi-frequency calibration for DOA estimation with distributed sensors. 2020. <a target=\"_blank\" href=\"https://hal.science/hal-02468904v1\">⟨hal-02468904⟩</a>",
"title_s":["[Technical Report] Multi-frequency calibration for DOA estimation with distributed sensors"],
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"citationFull_s":"Yassine Zniyed, Remy Boyer, André L. F. de Almeida, Gérard Favier. A TT-Based Hierarchical Framework for Decomposing High-Order Tensors. <i>SIAM Journal on Scientific Computing</i>, 2020, 42 (2), pp.A822-A848. <a target=\"_blank\" href=\"https://dx.doi.org/10.1137/18m1229973\">⟨10.1137/18m1229973⟩</a>. <a target=\"_blank\" href=\"https://hal.science/hal-02436368v1\">⟨hal-02436368⟩</a>",
"title_s":["A TT-Based Hierarchical Framework for Decomposing High-Order Tensors"],
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"citationFull_s":"Abdelhak Boudehane, Yassine Zniyed, Arthur Tenenhaus, Laurent Le Brusquet, Remy Boyer. Breaking the curse of dimensionality for coupled matrix-tensor factorization. <i>8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019)</i>, Dec 2019, Le Gosier, Guadeloupe. <a target=\"_blank\" href=\"https://dx.doi.org/10.1109/camsap45676.2019.9022462\">⟨10.1109/camsap45676.2019.9022462⟩</a>. <a target=\"_blank\" href=\"https://hal.science/hal-02417126v1\">⟨hal-02417126⟩</a>",
"title_s":["Breaking the curse of dimensionality for coupled matrix-tensor factorization"],
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"citationFull_s":"Yassine Zniyed, Remy Boyer, André L. F. de Almeida, Gérard Favier. Multidimensional Harmonic Retrieval Based on Vandermonde Tensor Train. <i>Signal Processing</i>, 2019, 163, <a target=\"_blank\" href=\"https://dx.doi.org/10.1016/j.sigpro.2019.05.007\">⟨10.1016/j.sigpro.2019.05.007⟩</a>. <a target=\"_blank\" href=\"https://hal.science/hal-02123112v1\">⟨hal-02123112⟩</a>",
"title_s":["Multidimensional Harmonic Retrieval Based on Vandermonde Tensor Train"],
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"citationRef_s":"<i>EUSIPCO 2019 - 27th European Signal Processing Conference</i>, Sep 2019, A Coruna, Spain. <a target=\"_blank\" href=\"https://dx.doi.org/10.23919/eusipco.2019.8902770\">⟨10.23919/eusipco.2019.8902770⟩</a>",
"citationFull_s":"Yassine Zniyed, Remy Boyer, André L. F. de Almeida, Gérard Favier. Tensor-Train Modeling for Mimo-OFDM Tensor Coding-and-Forwarding Relay Systems. <i>EUSIPCO 2019 - 27th European Signal Processing Conference</i>, Sep 2019, A Coruna, Spain. <a target=\"_blank\" href=\"https://dx.doi.org/10.23919/eusipco.2019.8902770\">⟨10.23919/eusipco.2019.8902770⟩</a>. <a target=\"_blank\" href=\"https://hal.science/hal-02146466v1\">⟨hal-02146466⟩</a>",
"title_s":["Tensor-Train Modeling for Mimo-OFDM Tensor Coding-and-Forwarding Relay Systems"],
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"citationFull_s":"A Boudehane, Remy Boyer, V. Ollier, M N El Korso, Anthony Ferrari, et al.. Performance bound for robust array calibration in radio interferometry. <i>GRETSI 2019 - XXVIIème Colloque francophone de traitement du signal et des images</i>, Aug 2019, Lille, France. <a target=\"_blank\" href=\"https://hal.science/hal-02141553v1\">⟨hal-02141553⟩</a>",
"title_s":["Performance bound for robust array calibration in radio interferometry"],
"authFullName_s":["A Boudehane","Remy Boyer","V. Ollier","M N El Korso","Anthony Ferrari","Pascal Larzabal"],
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"citationFull_s":"Yassine Zniyed, Sebastian Miron, Remy Boyer, David Brie. Uniqueness of tensor train decomposition with linear dependencies. <i>GRETSI 2019 - XXVIIème Colloque francophone de traitement du signal et des images</i>, Aug 2019, Lille, France. <a target=\"_blank\" href=\"https://hal.science/hal-02141554v1\">⟨hal-02141554⟩</a>",
"title_s":["Uniqueness of tensor train decomposition with linear dependencies"],
"authFullName_s":["Yassine Zniyed","Sebastian Miron","Remy Boyer","David Brie"],
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