Vincent Schellekens
Vincent Schellekens
Inria & ENS de Lyon
E-mail confirmado em ens-lyon.fr - Página inicial
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Quantized Compressive K-Means
V Schellekens, L Jacques
IEEE Signal Processing Letters 25 (8), 1211-1215, 2018
222018
Differentially private compressive k-means
V Schellekens, A Chatalic, F Houssiau, YA De Montjoye, L Jacques, ...
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
192019
Breaking the waves: asymmetric random periodic features for low-bitrate kernel machines
V Schellekens, L Jacques
Information and Inference: A Journal of the IMA, 2020
62020
Sketching datasets for large-scale learning (long version)
R Gribonval, A Chatalic, N Keriven, V Schellekens, L Jacques, P Schniter
arXiv preprint arXiv:2008.01839, 2020
52020
Compressive learning with privacy guarantees
A Chatalic, V Schellekens, F Houssiau, YA de Montjoye, L Jacques, ...
Information and Inference, 2021
42021
Compressive k-means with differential privacy
V Schellekens, A Chatalic, F Houssiau, YA de Montjoye, L Jacques, ...
SPARS 2019-Signal Processing with Adaptive Sparse Structured Representations …, 2019
32019
Compressive Classification (Machine Learning without learning)
V Schellekens, L Jacques
arXiv preprint arXiv:1812.01410, 2018
32018
Compressive clustering of high-dimensional datasets by 1-bit sketching
V Schellekens, L Jacques
PhD thesis, 2017
22017
Sketching Data Sets for Large-Scale Learning: Keeping only what you need
R Gribonval, A Chatalic, N Keriven, V Schellekens, L Jacques, P Schniter
IEEE Signal Processing Magazine 38 (5), 12-36, 2021
12021
Compressive Learning of Generative Networks
V Schellekens, L Jacques
28th European Symposium on Artificial Neural Networks, Computational …, 2020
12020
When compressive learning fails: blame the decoder or the sketch?
V Schellekens, L Jacques
arXiv preprint arXiv:2009.08273, 2020
12020
Taking the edge off quantization: projected back projection in dithered compressive sensing
C Xu, V Schellekens, L Jacques
2018 IEEE Statistical Signal Processing Workshop (SSP), 203-207, 2018
12018
Extending the Compressive Statistical Learning Framework: Quantization, Privacy, and Beyond
V Schellekens
UCLouvain, Belgium, 2021
2021
Asymmetric compressive learning guarantees with applications to quantized sketches
V Schellekens, L Jacques
arXiv preprint arXiv:2104.10061, 2021
2021
PYCLE: a Python Compressive Learning toolbox
V Schellekens
https://github.com/schellekensv/pycle, 2020
2020
Compressive k-means with differential privacy
F Houssiau, YA De Montjoye, V Schellekens, A Chatalic, L Jacques, ...
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