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11/25/2022
M^2M: A general method to perform various data analysis tasks from a differentially private sketch
Differential privacy is the standard privacy definition for performing a...
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05/17/2022
ROP inception: signal estimation with quadratic random sketching
Rank-one projections (ROP) of matrices and quadratic random sketching of...
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04/20/2021
Asymmetric compressive learning guarantees with applications to quantized sketches
The compressive learning framework reduces the computational cost of tra...
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09/14/2020
When compressive learning fails: blame the decoder or the sketch?
In compressive learning, a mixture model (a set of centroids or a Gaussi...
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08/04/2020
Sketching Datasets for Large-Scale Learning (long version)
This article considers "sketched learning," or "compressive learning," a...
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04/14/2020
Breaking the waves: asymmetric random periodic features for low-bitrate kernel machines
Many signal processing and machine learning applications are built from ...
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02/12/2020
Compressive Learning of Generative Networks
Generative networks implicitly approximate complex densities from their ...
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12/04/2018
Compressive Classification (Machine Learning without learning)
Compressive learning is a framework where (so far unsupervised) learning...
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05/11/2018
Taking the edge off quantization: projected back projection in dithered compressive sensing
Quantized compressive sensing (QCS) deals with the problem of representi...
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04/26/2018
