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Javier Fernandez-Marques
Javier Fernandez-Marques
Research Scientist, FlowerLabs
Verified email at cs.ox.ac.uk - Homepage
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Cited by
Cited by
Year
Flower: A friendly federated learning research framework
DJ Beutel, T Topal, A Mathur, X Qiu, J Fernandez-Marques, Y Gao, L Sani, ...
arXiv preprint arXiv:2007.14390, 2020
5552020
Degree-Quant: Quantization-Aware Training for Graph Neural Networks
SA Tailor, J Fernandez-Marques, ND Lane
International Conference on Learning Representations (ICLR), 2021
1372021
An Empirical study of Binary Neural Networks' Optimisation
M Alizadeh, J Fernández-Marqués, ND Lane, Y Gal
International Conference on Learning Representations (ICLR), 2019
932019
A first look into the carbon footprint of federated learning
X Qiu, T Parcollet, J Fernandez-Marques, PPB Gusmao, Y Gao, DJ Beutel, ...
Journal of Machine Learning Research 24 (129), 1-23, 2023
552023
ZeroFL: Efficient on-device training for federated learning with local sparsity
X Qiu, J Fernandez-Marques, PPB Gusmao, Y Gao, T Parcollet, ND Lane
arXiv preprint arXiv:2208.02507, 2022
382022
On-device federated learning with flower
A Mathur, DJ Beutel, PPB de Gusmao, J Fernandez-Marques, T Topal, ...
arXiv preprint arXiv:2104.03042, 2021
372021
Searching for Winograd-aware Quantized Networks
J Fernandez-Marques, PN Whatmough, A Mundy, M Mattina
Conference on Machine Learning and Systems (MLSys), 2020
372020
End-to-end speech recognition from federated acoustic models
Y Gao, T Parcollet, S Zaiem, J Fernandez-Marques, PPB de Gusmao, ...
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
362022
Deterministic Binary Filters for Convolutional Neural Networks.
VWS Tseng, S Bhattacharya, J Fernández-Marqués, M Alizadeh, C Tong, ...
International Joint Conference on Artificial Intelligence (IJCAI), 2018
162018
Federated Self-supervised Speech Representations: Are We There Yet?
Y Gao, J Fernandez-Marques, T Parcollet, A Mehrotra, ND Lane
arXiv preprint arXiv:2204.02804, 2022
132022
unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation
SI Venieris, J Fernandez-Marques, ND Lane
IEEE International Symposium on Field-Programmable Custom Computing Machines …, 2021
112021
On-the-fly deterministic binary filters for memory efficient keyword spotting applications on embedded devices
J Fernandez-Marques, VTS Tseng, S Bhattacharya, ND Lane
Proceedings of the 2nd International Workshop on Deep Learning for Mobile …, 2018
112018
BinaryCmd: Keyword Spotting with deterministic binary basis
J Fernandez-Marques, WST Vincent, S Bhattachara, ND Lane
Conference on Machine Learning and Systems (MLSys), 2018
82018
Match to win: Analysing sequences lengths for efficient self-supervised learning in speech and audio
Y Gaol, J Fernandez-Marques, T Parcollet, PPB de Gusmao, ND Lane
2022 IEEE Spoken Language Technology Workshop (SLT), 115-122, 2023
72023
Federated Learning for Inference at Anytime and Anywhere
Z Liu, D Li, J Fernandez-Marques, S Laskaridis, Y Gao, Ł Dudziak, SZ Li, ...
arXiv preprint arXiv:2212.04084, 2022
72022
FedorAS: Federated Architecture Search under system heterogeneity
L Dudziak, S Laskaridis, J Fernandez-Marques
arXiv preprint arXiv:2206.11239, 2022
72022
Deep learning on microcontrollers: a study on deployment costs and challenges
F Svoboda, J Fernandez-Marques, E Liberis, ND Lane
Proceedings of the 2nd European Workshop on Machine Learning and Systems, 54-63, 2022
72022
Characterization of the role of collagen network structure and composition in cancer cell migration
M Anguiano, C Castilla, M Maška, C Ederra, J Fernández-Marqués, ...
IEEE International Conference of Engineering in Medicine and Biology Society …, 2015
72015
Quantification of the 3D collagen network geometry in confocal reflection microscopy
M Maska, C Ederra, J Fernández-Marqués, A Muñoz-Barrutia, M Kozubek, ...
IEEE International Conference on Image Processing (ICIP), 2015
52015
Protea: Client profiling within federated systems using flower
W Zhao, X Qiu, J Fernandez-Marques, PPB de Gusmão, ND Lane
Proceedings of the 1st ACM Workshop on Data Privacy and Federated Learning …, 2022
42022
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