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Vincent Schellekens
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2020 – today
- 2023
- [c6]Rémi Delogne, Vincent Schellekens, Laurent Daudet, Laurent Jacques:
Signal Processing with Optical Quadratic Random Sketches. ICASSP 2023: 1-5 - 2022
- [j3]Vincent Schellekens, Laurent Jacques:
Asymmetric Compressive Learning Guarantees With Applications to Quantized Sketches. IEEE Trans. Signal Process. 70: 1348-1360 (2022) - [c5]Rémi Delogne, Vincent Schellekens, Laurent Jacques:
ROP inception: signal estimation with quadratic random sketching. ESANN 2022 - [c4]Florimond Houssiau, Vincent Schellekens, Antoine Chatalic, Shreyas Kumar Annamraju, Yves-Alexandre de Montjoye:
M2M: A General Method to Perform Various Data Analysis Tasks from a Differentially Private Sketch. STM 2022: 117-135 - [i10]Rémi Delogne, Vincent Schellekens, Laurent Jacques:
ROP inception: signal estimation with quadratic random sketching. CoRR abs/2205.08225 (2022) - [i9]Florimond Houssiau, Vincent Schellekens, Antoine Chatalic, Shreyas Kumar Annamraju, Yves-Alexandre de Montjoye:
M2M: A general method to perform various data analysis tasks from a differentially private sketch. CoRR abs/2211.14062 (2022) - 2021
- [b1]Vincent Schellekens:
Extending the compressive statistical learning framework: quantization, privacy and beyond. Catholic University of Louvain, Louvain-la-Neuve, Belgium, 2021 - [j2]Rémi Gribonval, Antoine Chatalic, Nicolas Keriven, Vincent Schellekens, Laurent Jacques, Philip Schniter:
Sketching Data Sets for Large-Scale Learning: Keeping only what you need. IEEE Signal Process. Mag. 38(5): 12-36 (2021) - [i8]Vincent Schellekens, Laurent Jacques:
Asymmetric compressive learning guarantees with applications to quantized sketches. CoRR abs/2104.10061 (2021) - 2020
- [c3]Vincent Schellekens, Laurent Jacques:
Compressive Learning of Generative Networks. ESANN 2020: 429-434 - [i7]Vincent Schellekens, Laurent Jacques:
Compressive Learning of Generative Networks. CoRR abs/2002.05095 (2020) - [i6]Vincent Schellekens, Laurent Jacques:
Breaking the waves: asymmetric random periodic features for low-bitrate kernel machines. CoRR abs/2004.06560 (2020) - [i5]Rémi Gribonval, Antoine Chatalic, Nicolas Keriven, Vincent Schellekens, Laurent Jacques, Philip Schniter:
Sketching Datasets for Large-Scale Learning (long version). CoRR abs/2008.01839 (2020) - [i4]Vincent Schellekens, Laurent Jacques:
When compressive learning fails: blame the decoder or the sketch? CoRR abs/2009.08273 (2020)
2010 – 2019
- 2019
- [c2]Vincent Schellekens, Antoine Chatalic, Florimond Houssiau, Yves-Alexandre de Montjoye, Laurent Jacques, Rémi Gribonval:
Differentially Private Compressive K-means. ICASSP 2019: 7933-7937 - 2018
- [j1]Vincent Schellekens, Laurent Jacques:
Quantized Compressive K-Means. IEEE Signal Process. Lett. 25(8): 1211-1215 (2018) - [c1]Chunlei Xu, Vincent Schellekens, Laurent Jacques:
Taking the Edge off Quantization: Projected Back Projection in Dithered Compressive Sensing. SSP 2018: 203-207 - [i3]Vincent Schellekens, Laurent Jacques:
Quantized Compressive K-Means. CoRR abs/1804.10109 (2018) - [i2]Chunlei Xu, Vincent Schellekens, Laurent Jacques:
Taking the edge off quantization: projected back projection in dithered compressive sensing. CoRR abs/1805.04348 (2018) - [i1]Vincent Schellekens, Laurent Jacques:
Compressive Classification (Machine Learning without learning). CoRR abs/1812.01410 (2018)
Coauthor Index
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