Gustavo Silva — accepted AI-conference papers

2020

Anomaly Detection in Mixed Time-Series Using A Convolutional Sparse Representation With Application To Spacecraft Health Monitoring

Barbara Pilastre, Gustavo Silva, Loïc Boussouf, Stéphane D'Escrivan, Paul Rodríguez, Jean-Yves Tourneret

ICASSP 2020accepted

This paper introduces a convolutional sparse model for anomaly detection in mixed continuous and discrete data. This model, referred to as C-ADDICT, builds upon the experiences of our previous ADDICT algorithm. It can handle discrete and continuous data jointly, is intrinsically shift-invariant, and…

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2018

Efficient Convolutional Dictionary Learning Using Partial Update Fast Iterative Shrinkage-Thresholding Algorithm

Gustavo Silva, Paul Rodríguez

ICASSP 2018accepted

Convolutional sparse representations allow modeling an entire image as an alternative to the more common independent patch-based formulations. Although many approaches have been proposed to efficiently solve the convolutional dictionary learning (CDL) problem, their computational performance is cons…

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2017

Fast convolutional sparse coding with separable filters

Gustavo Silva, Jorge Quesada, Paul Rodríguez, Brendt Wohlberg

ICASSP 2017accepted

Convolutional sparse representations (CSR) of images are receiving increasing attention as an alternative to the usual independent patch-wise application of standard sparse representations. For CSR the dictionary is a filter bank of non-separable 2D filters, and the representation itself can be view…

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