Javier Fernández-Marqués

Orcid: 0000-0003-3747-6523

According to our database1, Javier Fernández-Marqués authored at least 25 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2023
Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation.
ACM Trans. Design Autom. Electr. Syst., November, 2023

A First Look into the Carbon Footprint of Federated Learning.
J. Mach. Learn. Res., 2023

How Much Is Hidden in the NAS Benchmarks? Few-Shot Adaptation of a NAS Predictor.
CoRR, 2023

Are We There Yet? Product Quantization and its Hardware Acceleration.
CoRR, 2023

2022
Federated Learning for Inference at Anytime and Anywhere.
CoRR, 2022

Match to Win: Analysing Sequences Lengths for Efficient Self-supervised Learning in Speech and Audio.
CoRR, 2022

FedorAS: Federated Architecture Search under system heterogeneity.
CoRR, 2022

Match to Win: Analysing Sequences Lengths for Efficient Self-Supervised Learning in Speech and Audio.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

Federated Self-supervised Speech Representations: Are We There Yet?
Proceedings of the Interspeech 2022, 2022

ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity.
Proceedings of the Tenth International Conference on Learning Representations, 2022

End-to-End Speech Recognition from Federated Acoustic Models.
Proceedings of the IEEE International Conference on Acoustics, 2022

Protea: client profiling within federated systems using flower.
Proceedings of the 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network, 2022

Deep learning on microcontrollers: a study on deployment costs and challenges.
Proceedings of the EuroMLSys '22: Proceedings of the 2nd European Workshop on Machine Learning and Systems, Rennes, France, April 5, 2022

2021
End-to-End Speech Recognition from Federated Acoustic Models.
CoRR, 2021

On-device Federated Learning with Flower.
CoRR, 2021

A first look into the carbon footprint of federated learning.
CoRR, 2021

Degree-Quant: Quantization-Aware Training for Graph Neural Networks.
Proceedings of the 9th International Conference on Learning Representations, 2021

unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation.
Proceedings of the 29th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2021

2020
Searching for Winograd-aware Quantized Networks.
Proceedings of Machine Learning and Systems 2020, 2020

2019
An Empirical study of Binary Neural Networks' Optimisation.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
On-the-fly deterministic binary filters for memory efficient keyword spotting applications on embedded devices.
Proceedings of the 2nd International Workshop on Embedded and Mobile Deep Learning, 2018

Deterministic binary filters for keyword spotting applications.
Proceedings of the 16th Annual International Conference on Mobile Systems, 2018

Deterministic Binary Filters for Convolutional Neural Networks.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2015
Quantification of the 3D collagen network geometry in confocal reflection microscopy.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Characterization of the role of collagen network structure and composition in cancer cell migration.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015


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