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Luc Le Magoarou
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2020 – today
- 2024
- [j9]Antonin Rabault, Luc Le Magoarou, Jérôme Sol, George C. Alexandropoulos, Nir Shlezinger, H. Vincent Poor, Philipp del Hougne:
On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels. IEEE Trans. Wirel. Commun. 23(8): 10001-10014 (2024) - [c18]Baptiste Chatelier, Luc Le Magoarou, Vincent Corlay, Matthieu Criissière:
Model-Based Learning for Location-to-Channel Mapping. ICASSP 2024: 12836-12840 - [i23]Baptiste Chatelier, Vincent Corlay, Matthieu Crussière, Luc Le Magoarou:
Model-based learning for multi-antenna multi-frequency location-to-channel mapping. CoRR abs/2407.07719 (2024) - 2023
- [c17]Taha Yassine, Baptiste Chatelier, Vincent Corlay, Matthieu Crussière, Stéphane Paquelet, Olav Tirkkonen, Luc Le Magoarou:
Model-Based Deep Learning for Beam Prediction Based on a Channel Chart. ACSSC 2023: 1636-1640 - [c16]Baptiste Chatelier, Luc Le Magoarou, Getachew Redieteab:
Efficient Deep Unfolding for SISO-OFDM Channel Estimation. ICC 2023: 3450-3455 - [c15]José Miguel Mateos-Ramos, Christian Häger, Musa Furkan Keskin, Luc Le Magoarou, Henk Wymeersch:
Model-Driven End-to-End Learning for Integrated Sensing and Communication. ICC 2023: 5695-5700 - [i22]Antonin Rabault, Luc Le Magoarou, Jérôme Sol, George C. Alexandropoulos, Nir Shlezinger, H. Vincent Poor, Philipp del Hougne:
On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels. CoRR abs/2302.04993 (2023) - [i21]Baptiste Chatelier, Luc Le Magoarou, Vincent Corlay, Matthieu Crussière:
Model-based learning for location-to-channel mapping. CoRR abs/2308.14370 (2023) - [i20]Lucas Polo-López, Luc Le Magoarou, Romain Contreres, María García-Vigueras:
Model-based Deep Learning for High-Dimensional Periodic Structures. CoRR abs/2309.12223 (2023) - [i19]Taha Yassine, Luc Le Magoarou, Matthieu Crussière, Stéphane Paquelet:
Optimizing Multicarrier Multiantenna Systems for LoS Channel Charting. CoRR abs/2310.03762 (2023) - [i18]Taha Yassine, Baptiste Chatelier, Vincent Corlay, Matthieu Crussière, Stéphane Paquelet, Olav Tirkkonen, Luc Le Magoarou:
Model-based Deep Learning for Beam Prediction based on a Channel Chart. CoRR abs/2312.02239 (2023) - 2022
- [j8]Taha Yassine
, Luc Le Magoarou
:
mpNet: Variable Depth Unfolded Neural Network for Massive MIMO Channel Estimation. IEEE Trans. Wirel. Commun. 21(7): 5703-5714 (2022) - [c14]Luc Le Magoarou, Taha Yassine, Stéphane Paquelet, Matthieu Crussière:
Channel charting based beamforming. IEEECONF 2022: 1185-1189 - [c13]Luc Le Magoarou, Taha Yassine, Stéphane Paquelet, Matthieu Crussière:
Deep Learning for Location Based Beamforming with Nlos Channels. ICASSP 2022: 8812-8816 - [c12]Taha Yassine, Luc Le Magoarou, Stéphane Paquelet, Matthieu Crussière:
Leveraging triplet loss and nonlinear dimensionality reduction for on-the-fly channel charting. SPAWC 2022: 1-5 - [c11]Miltiadis C. Filippou, Vasiliki Lamprousi, Jafar Mohammadi, Mattia Merluzzi, Elif Ustundag Soykan, Tamás Borsos, Nandana Rajatheva, Nuwanthika Rajapaksha, Luc Le Magoarou, Pietro Piscione, András Benczúr, Quentin Lampin, Guillaume Larue, Dani Korpi, Pietro Ducange, Alessandro Renda, Hamed Farhadi, Johan Haraldson, Leonardo Gomes Baltar, Emilio Calvanese Strinati, Panagiotis Demestichas, Emrah Tomur:
Pervasive Artificial Intelligence in Next Generation Wireless: The Hexa-X Project Perspective. AI6G@WCCI 2022 - [i17]Luc Le Magoarou
, Taha Yassine, Stéphane Paquelet, Matthieu Crussière:
Deep learning for location based beamforming with NLOS channels. CoRR abs/2201.01386 (2022) - [i16]Taha Yassine, Luc Le Magoarou, Stéphane Paquelet, Matthieu Crussière:
Leveraging triplet loss and nonlinear dimensionality reduction for on-the-fly channel charting. CoRR abs/2204.13996 (2022) - [i15]Baptiste Chatelier, Luc Le Magoarou, Getachew Redieteab:
Efficient Deep Unfolding for SISO-OFDM Channel Estimation. CoRR abs/2210.06588 (2022) - [i14]Luc Le Magoarou, Taha Yassine, Stéphane Paquelet, Matthieu Crussière:
Channel charting based beamforming. CoRR abs/2212.12340 (2022) - 2021
- [j7]Luc Le Magoarou
:
Similarity-Based Prediction for Channel Mapping and User Positioning. IEEE Commun. Lett. 25(5): 1578-1582 (2021) - [j6]Luc Le Magoarou
:
Efficient Channel Charting via Phase-Insensitive Distance Computation. IEEE Wirel. Commun. Lett. 10(12): 2634-2638 (2021) - [i13]Luc Le Magoarou
:
Similarity-based prediction for channel mapping and user positioning. CoRR abs/2101.05217 (2021) - [i12]Luc Le Magoarou
:
Efficient channel charting via phase-insensitive distance computation. CoRR abs/2104.13184 (2021) - 2020
- [j5]Luc Le Magoarou
, Stéphane Paquelet
:
Channel Estimation: Unified View of Optimal Performance and Pilot Sequences. IEEE Trans. Signal Process. 68: 5588-5601 (2020) - [c10]Vincent Savaux, Luc Le Magoarou:
On the Computation of Integrals of Bivariate Gaussian Distribution. ISCC 2020: 1-6 - [i11]Taha Yassine, Luc Le Magoarou
:
mpNet: variable depth unfolded neural network for massive MIMO channel estimation. CoRR abs/2008.04088 (2020)
2010 – 2019
- 2019
- [j4]Samer Bazzi
, Stelios Stefanatos, Luc Le Magoarou
, Salah Eddine Hajri, Mohamad Assaad, Stéphane Paquelet, Gerhard Wunder, Wen Xu:
Exploiting the Massive MIMO Channel Structural Properties for Minimization of Channel Estimation Error and Training Overhead. IEEE Access 7: 32434-32452 (2019) - [c9]Luc Le Magoarou, Antoine Le Calvez, Stéphane Paquelet:
Massive MIMO Channel Estimation taking into account spherical waves. SPAWC 2019: 1-5 - [i10]Luc Le Magoarou
, Stéphane Paquelet:
Performance of MIMO channel estimation with a physical model. CoRR abs/1902.07031 (2019) - 2018
- [j3]Luc Le Magoarou
, Rémi Gribonval, Nicolas Tremblay
:
Approximate Fast Graph Fourier Transforms via Multilayer Sparse Approximations. IEEE Trans. Signal Inf. Process. over Networks 4(2): 407-420 (2018) - [c8]Luc Le Magoarou, Stéphane Paquelet:
Parametric Channel Estimation for Massive MIMO. SSP 2018: 30-34 - [c7]Matthieu Roy, Stéphane Paquelet, Luc Le Magoarou
, Matthieu Crussière:
MIMO Channel Hardening for Ray-based Models. WiMob 2018: 1-7 - [i9]Matthieu Roy, Stéphane Paquelet, Luc Le Magoarou
, Matthieu Crussière:
MIMO Channel Hardening: A Physical Model based Analysis. CoRR abs/1804.07491 (2018) - [i8]Luc Le Magoarou
, Stéphane Paquelet:
Bias-variance tradeoff in MIMO channel estimation. CoRR abs/1804.07529 (2018) - [i7]Antoine Le Calvez, Luc Le Magoarou
, Stéphane Paquelet:
Massive MIMO channel estimation taking into account spherical waves. CoRR abs/1811.05669 (2018) - 2017
- [c6]Luc Le Magoarou, Nicolas Tremblay, Rémi Gribonval:
Analyzing the approximation error of the fast graph Fourier transform. ACSSC 2017: 45-49 - [i6]Luc Le Magoarou
, Stéphane Paquelet:
Parametric channel estimation for massive MIMO. CoRR abs/1710.08214 (2017) - [i5]Luc Le Magoarou, Nicolas Tremblay, Rémi Gribonval:
Analyzing the Approximation Error of the Fast Graph Fourier Transform. CoRR abs/1711.00386 (2017) - 2016
- [b1]Luc Le Magoarou:
Matrices efficientes pour le traitement du signal et l'apprentissage automatique. (Efficient matrices for signal processing and machine learning). INSA de Rennes, France, 2016 - [j2]Luc Le Magoarou
, Rémi Gribonval:
Flexible Multilayer Sparse Approximations of Matrices and Applications. IEEE J. Sel. Top. Signal Process. 10(4): 688-700 (2016) - [c5]Luc Le Magoarou, Rémi Gribonval:
Are there approximate fast fourier transforms on graphs? ICASSP 2016: 4811-4815 - [i4]Luc Le Magoarou
, Rémi Gribonval, Nicolas Tremblay:
Approximate Fast Fourier Transforms on graphs via multi-layer sparse approximations. CoRR abs/1612.04542 (2016) - 2015
- [j1]Luc Le Magoarou, Alexey Ozerov, Ngoc Q. K. Duong:
Text-Informed Audio Source Separation. Example-Based Approach Using Non-Negative Matrix Partial Co-Factorization. J. Signal Process. Syst. 79(2): 117-131 (2015) - [c4]Luc Le Magoarou, Rémi Gribonval, Alexandre Gramfort
:
FAμST: Speeding up linear transforms for tractable inverse problems. EUSIPCO 2015: 2516-2520 - [c3]Luc Le Magoarou
, Rémi Gribonval:
Chasing butterflies: In search of efficient dictionaries. ICASSP 2015: 3287-3291 - [i3]Luc Le Magoarou
, Rémi Gribonval:
Flexible Multi-layer Sparse Approximations of Matrices and Applications. CoRR abs/1506.07300 (2015) - 2014
- [i2]Luc Le Magoarou
, Rémi Gribonval:
Learning computationally efficient dictionaries and their implementation as fast transforms. CoRR abs/1406.5388 (2014) - [i1]Laurent Jacques, Christophe De Vleeschouwer, Yannick Boursier, Prasad Sudhakar, C. De Mol, Aleksandra Pizurica, Sandrine Anthoine, Pierre Vandergheynst, Pascal Frossard, Cagdas Bilen, Srdan Kitic, Nancy Bertin, Rémi Gribonval, Nicolas Boumal, Bamdev Mishra, Pierre-Antoine Absil, Rodolphe Sepulchre, Shaun Bundervoet, Colas Schretter, Ann Dooms, Peter Schelkens, Olivier Chabiron, François Malgouyres, Jean-Yves Tourneret, Nicolas Dobigeon, Pierre Chainais, Cédric Richard, Bruno Cornelis, Ingrid Daubechies, David B. Dunson, Marie Danková, Pavel Rajmic, Kévin Degraux, Valerio Cambareri, Bert Geelen, Gauthier Lafruit, Gianluca Setti, Jean-François Determe, Jérôme Louveaux, François Horlin, Angélique Drémeau, Patrick Héas, Cédric Herzet, Vincent Duval, Gabriel Peyré, Alhussein Fawzi, Mike E. Davies, Nicolas Gillis, Stephen A. Vavasis, Charles Soussen, Luc Le Magoarou, Jingwei Liang, Jalal Fadili, Antoine Liutkus, David Martina, Sylvain Gigan, Laurent Daudet, Mauro Maggioni, Stanislav Minsker, Nate Strawn, C. Mory, Fred Maurice Ngolè Mboula, Jean-Luc Starck, Ignace Loris, Samuel Vaiter, Mohammad Golbabaee, Dejan Vukobratovic:
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14). CoRR abs/1410.0719 (2014) - 2013
- [c2]Arnaud Breloy, Luc Le Magoarou, Guillaume Ginolhac, Frédéric Pascal, Philippe Forster:
Maximum likelihood estimation of clutter subspace in non homogeneous noise context. EUSIPCO 2013: 1-5 - [c1]Luc Le Magoarou, Alexey Ozerov, Ngoc Q. K. Duong:
Text-informed audio source separation using nonnegative matrix partial co-factorization. MLSP 2013: 1-6
Coauthor Index
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last updated on 2024-08-22 20:50 CEST by the dblp team
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