Vincent Schellekens
Title
Cited by
Cited by
Year
Quantized Compressive K-Means
V Schellekens, L Jacques
IEEE Signal Processing Letters 25 (8), 1211-1215, 2018
162018
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
122019
Compressive Learning with Privacy Guarantees
A Chatalic, V Schellekens, F Houssiau, YA de Montjoye, L Jacques, ...
22020
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
22019
Compressive clustering of high-dimensional datasets by 1-bit sketching
V Schellekens, L Jacques
PhD thesis, 2017
22017
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
12020
Breaking the waves: asymmetric random periodic features for low-bitrate kernel machines
V Schellekens, L Jacques
arXiv preprint arXiv:2004.06560, 2020
12020
Compressive Classification (Machine Learning without learning)
V Schellekens, L Jacques
arXiv preprint arXiv:1812.01410, 2018
12018
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
Compressive Learning of Generative Networks
V Schellekens, L Jacques
28th European Symposium on Artificial Neural Networks, Computational …, 2020
2020
When compressive learning fails: blame the decoder or the sketch?
V Schellekens, L Jacques
arXiv preprint arXiv:2009.08273, 2020
2020
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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