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07/15/2023
Theoretical Analysis of Binary Masks in Snapshot Compressive Imaging Systems
Snapshot compressive imaging (SCI) systems have gained significant atten...
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09/04/2022
Incremental maximum likelihood estimation for efficient adaptive filtering
Adaptive filtering is a well-known problem with a wide range of applicat...
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07/31/2021
Compressed sensing in the presence of speckle noise
The problem of recovering a structured signal from its linear measuremen...
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02/15/2019
Efficient Deep Learning of GMMs
We show that a collection of Gaussian mixture models (GMMs) in R^n can b...
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01/17/2019
Denoising of structured random processes
Denoising stationary process (X_i)_i ∈ Z corrupted by additive white Gau...
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01/15/2019
Using auto-encoders for solving ill-posed linear inverse problems
Compressed sensing algorithms recover a signal from its under-determined...
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08/10/2018
Snapshot compressed sensing: performance bounds and algorithms
Snapshot compressed sensing (CS) refers to compressive imaging systems w...
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01/03/2018
Theoretical links between universal and Bayesian compressed sensing algorithms
Quantized maximum a posteriori (Q-MAP) is a recently-proposed Bayesian c...
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12/19/2017
Linear Time Clustering for High Dimensional Mixtures of Gaussian Clouds
Clustering mixtures of Gaussian distributions is a fundamental and chall...
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12/08/2017
