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Cédric Gouy-Pailler
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2020 – today
- 2024
- [c24]Fabiola Espinoza Castellon, Eduardo Fernandes Montesuma, Fred Maurice Ngolè Mboula, Aurélien Mayoue, Antoine Souloumiac, Cédric Gouy-Pailler:
Federated Dataset Dictionary Learning for Multi-Source Domain Adaptation. ICASSP 2024: 5610-5614 - [i19]Eduardo Fernandes Montesuma, Fabiola Espinoza Castellon, Fred Ngolè Mboula, Aurélien Mayoue, Antoine Souloumiac, Cédric Gouy-Pailler:
Dataset Dictionary Learning in a Wasserstein Space for Federated Domain Adaptation. CoRR abs/2407.11647 (2024) - 2023
- [c23]Arnaud Grivet Sébert, Marina Checri, Oana Stan, Renaud Sirdey, Cédric Gouy-Pailler:
Combining homomorphic encryption and differential privacy in federated learning. PST 2023: 1-7 - [c22]Fabiola Espinoza Castellon, Deepika Singh, Aurélien Mayoue, Cédric Gouy-Pailler:
FUBA: Federated Uncovering of Backdoor Attacks for Heterogeneous Data. TPS-ISA 2023: 55-63 - [c21]Arnaud Grivet Sébert, Martin Zuber, Oana Stan, Renaud Sirdey, Cédric Gouy-Pailler:
A Probabilistic Design for Practical Homomorphic Majority Voting with Intrinsic Differential Privacy. WAHC@CCS 2023: 47-58 - [i18]Arnaud Grivet Sébert, Martin Zuber, Oana Stan, Renaud Sirdey, Cédric Gouy-Pailler:
When approximate design for fast homomorphic computation provides differential privacy guarantees. CoRR abs/2304.02959 (2023) - [i17]Fabiola Espinosa Castellon, Eduardo Fernandes Montesuma, Fred Maurice Ngolè Mboula, Aurélien Mayoue, Antoine Souloumiac, Cédric Gouy-Pailler:
Federated Dataset Dictionary Learning for Multi-Source Domain Adaptation. CoRR abs/2309.07670 (2023) - 2022
- [j6]Rafael Pinot, Laurent Meunier, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif:
On the robustness of randomized classifiers to adversarial examples. Mach. Learn. 111(9): 3425-3457 (2022) - [c20]Abbass Madi, Oana Stan, Renaud Sirdey, Cédric Gouy-Pailler:
SecTL: Secure and Verifiable Transfer Learning-based inference. ICISSP 2022: 220-229 - [c19]Fabiola Espinoza Castellon, Aurélien Mayoue, Jacques-Henri Sublemontier, Cédric Gouy-Pailler:
Federated learning with incremental clustering for heterogeneous data. IJCNN 2022: 1-8 - [i16]Arnaud Grivet Sébert, Renaud Sirdey, Oana Stan, Cédric Gouy-Pailler:
Protecting Data from all Parties: Combining FHE and DP in Federated Learning. CoRR abs/2205.04330 (2022) - [i15]Fabiola Espinoza Castellon, Aurélien Mayoue, Jacques-Henri Sublemontier, Cédric Gouy-Pailler:
Federated learning with incremental clustering for heterogeneous data. CoRR abs/2206.08752 (2022) - [i14]Pierre-Emmanuel Clet, Martin Zuber, Aymen Boudguiga, Renaud Sirdey, Cédric Gouy-Pailler:
Putting up the swiss army knife of homomorphic calculations by means of TFHE functional bootstrapping. IACR Cryptol. ePrint Arch. 2022: 149 (2022) - 2021
- [j5]Arnaud Grivet Sébert, Rafael Pinot, Martin Zuber, Cédric Gouy-Pailler, Renaud Sirdey:
SPEED: secure, PrivatE, and efficient deep learning. Mach. Learn. 110(4): 675-694 (2021) - [i13]Rafael Pinot, Laurent Meunier, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif:
On the robustness of randomized classifiers to adversarial examples. CoRR abs/2102.10875 (2021) - 2020
- [c18]Sandra Garcia-Rodriguez, Mohammad Alshaer, Cédric Gouy-Pailler:
STREAMER: A Powerful Framework for Continuous Learning in Data Streams. CIKM 2020: 3385-3388 - [c17]Mohammad Alshaer, Sandra Garcia-Rodriguez, Cédric Gouy-Pailler:
Detecting Anomalies from Streaming Time Series using Matrix Profile and Shapelets Learning. ICTAI 2020: 376-383 - [i12]Arnaud Grivet Sébert, Rafael Pinot, Martin Zuber, Cédric Gouy-Pailler, Renaud Sirdey:
SPEED: Secure, PrivatE, and Efficient Deep learning. CoRR abs/2006.09475 (2020)
2010 – 2019
- 2019
- [c16]Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Theoretical evidence for adversarial robustness through randomization. NeurIPS 2019: 11838-11848 - [i11]Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. CoRR abs/1902.01148 (2019) - [i10]Rafael Pinot, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
A unified view on differential privacy and robustness to adversarial examples. CoRR abs/1906.07982 (2019) - 2018
- [c15]Oana Stan, Renaud Sirdey, Cédric Gouy-Pailler, Pierre Blanchart, Amira Ben Hamida, Mohamed-Haykel Zayani:
Privacy-Preserving Tax Calculations in Smart Cities by Means of Inner-Product Functional Encryption. CSNet 2018: 1-8 - [c14]Anne Morvan, Antoine Souloumiac, Cédric Gouy-Pailler, Jamal Atif:
Streaming Binary Sketching Based on Subspace Tracking and Diagonal Uniformization. ICASSP 2018: 2421-2425 - [c13]Anne Morvan, Krzysztof Choromanski, Cédric Gouy-Pailler, Jamal Atif:
Graph sketching-based Space-efficient Data Clustering. SDM 2018: 10-18 - [c12]Rafael Pinot, Anne Morvan, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Graph-based Clustering under Differential Privacy. UAI 2018: 329-338 - [i9]Anne Morvan, Antoine Souloumiac, Krzysztof Choromanski, Cédric Gouy-Pailler, Jamal Atif:
On the Needs for Rotations in Hypercubic Quantization Hashing. CoRR abs/1802.03936 (2018) - [i8]Rafael Pinot, Anne Morvan, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Graph-based Clustering under Differential Privacy. CoRR abs/1803.03831 (2018) - 2017
- [j4]Yoann Isaac, Quentin Barthélemy, Cédric Gouy-Pailler, Michèle Sebag, Jamal Atif:
Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations. Signal Process. 130: 389-402 (2017) - [c11]Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif:
Structured adaptive and random spinners for fast machine learning computations. AISTATS 2017: 1020-1029 - [c10]Pierre Blanchart, Cédric Gouy-Pailler:
WHODID: Web-Based Interface for Human-Assisted Factory Operations in Fault Detection, Identification and Diagnosis. ECML/PKDD (3) 2017: 437-441 - [i7]Anne Morvan, Krzysztof Choromanski, Cédric Gouy-Pailler, Jamal Atif:
Graph sketching-based Massive Data Clustering. CoRR abs/1703.02375 (2017) - [i6]Anne Morvan, Antoine Souloumiac, Cédric Gouy-Pailler, Jamal Atif:
Streaming Binary Sketching based on Subspace Tracking and Diagonal Uniformization. CoRR abs/1705.07661 (2017) - 2016
- [j3]Flore Harle, Florent Chatelain, Cédric Gouy-Pailler, Sophie Achard:
Bayesian Model for Multiple Change-Points Detection in Multivariate Time Series. IEEE Trans. Signal Process. 64(16): 4351-4362 (2016) - [i5]Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Tamás Sarlós, Jamal Atif:
TripleSpin - a generic compact paradigm for fast machine learning computations. CoRR abs/1605.09046 (2016) - [i4]Yoann Isaac, Quentin Barthélemy, Cédric Gouy-Pailler, Michèle Sebag, Jamal Atif:
Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations. CoRR abs/1609.09525 (2016) - [i3]Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif:
Structured adaptive and random spinners for fast machine learning computations. CoRR abs/1610.06209 (2016) - 2014
- [c9]Flore Harle, Florent Chatelain, Cédric Gouy-Pailler, Sophie Achard:
Rank-based multiple change-point detection in multivariate time series. EUSIPCO 2014: 1337-1341 - 2013
- [c8]Yoann Isaac, Quentin Barthélemy, Jamal Atif, Cédric Gouy-Pailler, Michèle Sebag:
Multi-dimensional sparse structured signal approximation using split bregman iterations. ICASSP 2013: 3826-3830 - [c7]Olaf Kouamo, Cédric Gouy-Pailler:
Multi-scale test procedure for non-stationarity in short and long memory time series. ICASSP 2013: 5368-5372 - [c6]Boujemaa Ait-El-Fquih, Cédric Gouy-Pailler:
Backward hidden Markov chain for outlier-robust filtering and fixed-interval smoothing. ICASSP 2013: 5504-5508 - [i2]Quentin Barthélemy, Cédric Gouy-Pailler, Yoann Isaac, Antoine Souloumiac, Anthony Larue, Jérôme I. Mars:
Multivariate Temporal Dictionary Learning for EEG. CoRR abs/1303.0742 (2013) - [i1]Yoann Isaac, Quentin Barthélemy, Jamal Atif, Cédric Gouy-Pailler, Michèle Sebag:
Multi-dimensional sparse structured signal approximation using split Bregman iterations. CoRR abs/1303.5197 (2013) - 2012
- [c5]Anthony Mouraud, Quentin Barthélemy, Aurélien Mayoue, Cédric Gouy-Pailler, Anthony Larue, Hélène Paugam-Moisy:
From neuronal cost-based metrics towards sparse coded signals classification. ESANN 2012 - 2011
- [j2]Cédric Gouy-Pailler, Michèle Sebag, Anthony Larue, Antoine Souloumiac:
Single trial variability in brain-computer interfaces based on motor imagery: Learning in the presence of labeling noise. Int. J. Imaging Syst. Technol. 21(2): 148-157 (2011) - 2010
- [j1]Cédric Gouy-Pailler, Marco Congedo, Clemens Brunner, Christian Jutten, Gert Pfurtscheller:
Nonstationary Brain Source Separation for Multiclass Motor Imagery. IEEE Trans. Biomed. Eng. 57(2): 469-478 (2010)
2000 – 2009
- 2009
- [b1]Cédric Gouy-Pailler:
Vers une modélisation dynamique de l'activité cérébrale pour la conception d'interfaces cerveau-machines asynchrones. (Toward dynamical models of brain activity for the design of brain-computer interfaces). Joseph Fourier University, Grenoble, France, 2009 - [c4]Cédric Gouy-Pailler, Jérémie Mattout, Marco Congedo, Christian Jutten:
Uncued brain-computer interfaces: a variational hidden markov model of mental state dynamics. ESANN 2009 - [c3]Cédric Gouy-Pailler, Reza Sameni, Marco Congedo, Christian Jutten:
Iterative Subspace Decomposition for Ocular Artifact Removal from EEG Recordings. ICA 2009: 419-426 - 2008
- [c2]Cédric Gouy-Pailler, Marco Congedo, Christian Jutten, Clemens Brunner, Gert Pfurtscheller:
Model-based source separation for multi-class motor imagery. EUSIPCO 2008: 1-5 - 2007
- [c1]Cédric Gouy-Pailler, Sophie Zijp-Rouzier, Sylvie Vidal, Denis Chêne:
A Haptic Based Interface to Ease Visually Impaired Pupils' Inclusion in Geometry Lessons. HCI (7) 2007: 598-606
Coauthor Index
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last updated on 2024-08-25 19:12 CEST by the dblp team
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