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Statistical Signal Processing

ROBUST M-ESTIMATION BASED MATRIX COMPLETION


Conventional approaches to matrix completion are sensitive to outliers and impulsive noise. This paper develops robust and computationally efficient M-estimation based matrix completion algorithms. By appropriately arranging the observed entries, and then applying alternating minimization, the robust matrix completion problem is converted into a set of regression M-estimation problems. Making use of differ- entiable loss functions, the proposed algorithm overcomes a weakness of the lp-loss (p ≤ 1), which easily gets stuck in an inferior point.

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Authors:
Michael Muma, Wen-Jun Zeng, Abdelhak M. Zoubir
Submitted On:
27 May 2019 - 11:28am
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[1] Michael Muma, Wen-Jun Zeng, Abdelhak M. Zoubir, "ROBUST M-ESTIMATION BASED MATRIX COMPLETION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4561. Accessed: Aug. 18, 2019.
@article{4561-19,
url = {http://sigport.org/4561},
author = {Michael Muma; Wen-Jun Zeng; Abdelhak M. Zoubir },
publisher = {IEEE SigPort},
title = {ROBUST M-ESTIMATION BASED MATRIX COMPLETION},
year = {2019} }
TY - EJOUR
T1 - ROBUST M-ESTIMATION BASED MATRIX COMPLETION
AU - Michael Muma; Wen-Jun Zeng; Abdelhak M. Zoubir
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4561
ER -
Michael Muma, Wen-Jun Zeng, Abdelhak M. Zoubir. (2019). ROBUST M-ESTIMATION BASED MATRIX COMPLETION. IEEE SigPort. http://sigport.org/4561
Michael Muma, Wen-Jun Zeng, Abdelhak M. Zoubir, 2019. ROBUST M-ESTIMATION BASED MATRIX COMPLETION. Available at: http://sigport.org/4561.
Michael Muma, Wen-Jun Zeng, Abdelhak M. Zoubir. (2019). "ROBUST M-ESTIMATION BASED MATRIX COMPLETION." Web.
1. Michael Muma, Wen-Jun Zeng, Abdelhak M. Zoubir. ROBUST M-ESTIMATION BASED MATRIX COMPLETION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4561

Improving Graph Trend Filtering with Non-Convex Penalties


In this paper, we study the denoising of piecewise smooth graph sig-nals that exhibit inhomogeneous levels of smoothness over a graph. We extend the graph trend filtering framework to a family of non-convex regularizers that exhibit superior recovery performance overexisting convex ones. We present theoretical results in the form ofasymptotic error rates for both generic and specialized graph models. We further present an ADMM-based algorithm to solve the proposedoptimization problem and analyze its convergence.

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Authors:
Rohan Varma, Jelena Kovačević
Submitted On:
9 June 2019 - 8:24pm
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[1] Rohan Varma, Jelena Kovačević, "Improving Graph Trend Filtering with Non-Convex Penalties", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4551. Accessed: Aug. 18, 2019.
@article{4551-19,
url = {http://sigport.org/4551},
author = {Rohan Varma; Jelena Kovačević },
publisher = {IEEE SigPort},
title = {Improving Graph Trend Filtering with Non-Convex Penalties},
year = {2019} }
TY - EJOUR
T1 - Improving Graph Trend Filtering with Non-Convex Penalties
AU - Rohan Varma; Jelena Kovačević
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4551
ER -
Rohan Varma, Jelena Kovačević. (2019). Improving Graph Trend Filtering with Non-Convex Penalties. IEEE SigPort. http://sigport.org/4551
Rohan Varma, Jelena Kovačević, 2019. Improving Graph Trend Filtering with Non-Convex Penalties. Available at: http://sigport.org/4551.
Rohan Varma, Jelena Kovačević. (2019). "Improving Graph Trend Filtering with Non-Convex Penalties." Web.
1. Rohan Varma, Jelena Kovačević. Improving Graph Trend Filtering with Non-Convex Penalties [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4551

Fusing Eigenvalues

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Authors:
Shahab Basiri, Esa Ollila, Gordana Drašković, Frédéric Pascal
Submitted On:
16 May 2019 - 12:25pm
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[1] Shahab Basiri, Esa Ollila, Gordana Drašković, Frédéric Pascal, "Fusing Eigenvalues", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4452. Accessed: Aug. 18, 2019.
@article{4452-19,
url = {http://sigport.org/4452},
author = {Shahab Basiri; Esa Ollila; Gordana Drašković; Frédéric Pascal },
publisher = {IEEE SigPort},
title = {Fusing Eigenvalues},
year = {2019} }
TY - EJOUR
T1 - Fusing Eigenvalues
AU - Shahab Basiri; Esa Ollila; Gordana Drašković; Frédéric Pascal
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4452
ER -
Shahab Basiri, Esa Ollila, Gordana Drašković, Frédéric Pascal. (2019). Fusing Eigenvalues. IEEE SigPort. http://sigport.org/4452
Shahab Basiri, Esa Ollila, Gordana Drašković, Frédéric Pascal, 2019. Fusing Eigenvalues. Available at: http://sigport.org/4452.
Shahab Basiri, Esa Ollila, Gordana Drašković, Frédéric Pascal. (2019). "Fusing Eigenvalues." Web.
1. Shahab Basiri, Esa Ollila, Gordana Drašković, Frédéric Pascal. Fusing Eigenvalues [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4452

Model Change Detection with Application to Machine Learning

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10 May 2019 - 4:47pm
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[1] , "Model Change Detection with Application to Machine Learning", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4406. Accessed: Aug. 18, 2019.
@article{4406-19,
url = {http://sigport.org/4406},
author = { },
publisher = {IEEE SigPort},
title = {Model Change Detection with Application to Machine Learning},
year = {2019} }
TY - EJOUR
T1 - Model Change Detection with Application to Machine Learning
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4406
ER -
. (2019). Model Change Detection with Application to Machine Learning. IEEE SigPort. http://sigport.org/4406
, 2019. Model Change Detection with Application to Machine Learning. Available at: http://sigport.org/4406.
. (2019). "Model Change Detection with Application to Machine Learning." Web.
1. . Model Change Detection with Application to Machine Learning [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4406

PERFORMANCE BOUND FOR BLIND EXTRACTION OF NON-GAUSSIAN COMPLEX-VALUED VECTOR COMPONENT FROM GAUSSIAN BACKGROUND


Independent Vector Extraction aims at the joint blind source extraction of $K$ dependent signals of interest (SOI) from $K$ mixtures (one signal from one mixture). Similarly to Independent Component/Vector Analysis (ICA/IVA), the SOIs are assumed to be independent of the other signals in the mixture. Compared to IVA, the (de-)mixing IVE model is reduced in the number of parameters for the extraction problem. The SOIs are assumed to be non-Gaussian or noncircular Gaussian, while the other signals are modeled as circular Gaussian.

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10 May 2019 - 4:06pm
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[1] , "PERFORMANCE BOUND FOR BLIND EXTRACTION OF NON-GAUSSIAN COMPLEX-VALUED VECTOR COMPONENT FROM GAUSSIAN BACKGROUND", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4399. Accessed: Aug. 18, 2019.
@article{4399-19,
url = {http://sigport.org/4399},
author = { },
publisher = {IEEE SigPort},
title = {PERFORMANCE BOUND FOR BLIND EXTRACTION OF NON-GAUSSIAN COMPLEX-VALUED VECTOR COMPONENT FROM GAUSSIAN BACKGROUND},
year = {2019} }
TY - EJOUR
T1 - PERFORMANCE BOUND FOR BLIND EXTRACTION OF NON-GAUSSIAN COMPLEX-VALUED VECTOR COMPONENT FROM GAUSSIAN BACKGROUND
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4399
ER -
. (2019). PERFORMANCE BOUND FOR BLIND EXTRACTION OF NON-GAUSSIAN COMPLEX-VALUED VECTOR COMPONENT FROM GAUSSIAN BACKGROUND. IEEE SigPort. http://sigport.org/4399
, 2019. PERFORMANCE BOUND FOR BLIND EXTRACTION OF NON-GAUSSIAN COMPLEX-VALUED VECTOR COMPONENT FROM GAUSSIAN BACKGROUND. Available at: http://sigport.org/4399.
. (2019). "PERFORMANCE BOUND FOR BLIND EXTRACTION OF NON-GAUSSIAN COMPLEX-VALUED VECTOR COMPONENT FROM GAUSSIAN BACKGROUND." Web.
1. . PERFORMANCE BOUND FOR BLIND EXTRACTION OF NON-GAUSSIAN COMPLEX-VALUED VECTOR COMPONENT FROM GAUSSIAN BACKGROUND [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4399

Updates In Bayesian Filtering By Continuous Projections On A Manifold Of Densities


In this paper, we develop a novel method for approximate continuous-discrete Bayesian filtering. The projection filtering framework is exploited to develop accurate approximations of posterior distributions within parametric classes of probability distributions. This is done by formulating an ordinary differential equation for the posterior distribution that has the prior as initial value and hits the exact posterior after a unit of

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Authors:
Filip Tronarp, Simo Särkkä
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10 May 2019 - 10:47am
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[1] Filip Tronarp, Simo Särkkä, "Updates In Bayesian Filtering By Continuous Projections On A Manifold Of Densities", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4349. Accessed: Aug. 18, 2019.
@article{4349-19,
url = {http://sigport.org/4349},
author = {Filip Tronarp; Simo Särkkä },
publisher = {IEEE SigPort},
title = {Updates In Bayesian Filtering By Continuous Projections On A Manifold Of Densities},
year = {2019} }
TY - EJOUR
T1 - Updates In Bayesian Filtering By Continuous Projections On A Manifold Of Densities
AU - Filip Tronarp; Simo Särkkä
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4349
ER -
Filip Tronarp, Simo Särkkä. (2019). Updates In Bayesian Filtering By Continuous Projections On A Manifold Of Densities. IEEE SigPort. http://sigport.org/4349
Filip Tronarp, Simo Särkkä, 2019. Updates In Bayesian Filtering By Continuous Projections On A Manifold Of Densities. Available at: http://sigport.org/4349.
Filip Tronarp, Simo Särkkä. (2019). "Updates In Bayesian Filtering By Continuous Projections On A Manifold Of Densities." Web.
1. Filip Tronarp, Simo Särkkä. Updates In Bayesian Filtering By Continuous Projections On A Manifold Of Densities [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4349

Chained Compressed Sensing for IoT Node Security


Compressed sensing can be used to yield both compression and a limited form of security to the readings of sensors. This can be most useful when designing the low-resources sensor nodes that are the backbone of IoT applications. Here, we propose to use chaining of subsequent plaintexts to improve the robustness of CS-based encryption against ciphertext-only attacks, known-plaintext attacks and man-in-the-middle attacks.

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Authors:
Mauro Mangia, Alex Marchioni, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti
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10 May 2019 - 10:34am
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[1] Mauro Mangia, Alex Marchioni, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti, "Chained Compressed Sensing for IoT Node Security", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4343. Accessed: Aug. 18, 2019.
@article{4343-19,
url = {http://sigport.org/4343},
author = {Mauro Mangia; Alex Marchioni; Fabio Pareschi; Riccardo Rovatti; Gianluca Setti },
publisher = {IEEE SigPort},
title = {Chained Compressed Sensing for IoT Node Security},
year = {2019} }
TY - EJOUR
T1 - Chained Compressed Sensing for IoT Node Security
AU - Mauro Mangia; Alex Marchioni; Fabio Pareschi; Riccardo Rovatti; Gianluca Setti
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4343
ER -
Mauro Mangia, Alex Marchioni, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti. (2019). Chained Compressed Sensing for IoT Node Security. IEEE SigPort. http://sigport.org/4343
Mauro Mangia, Alex Marchioni, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti, 2019. Chained Compressed Sensing for IoT Node Security. Available at: http://sigport.org/4343.
Mauro Mangia, Alex Marchioni, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti. (2019). "Chained Compressed Sensing for IoT Node Security." Web.
1. Mauro Mangia, Alex Marchioni, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti. Chained Compressed Sensing for IoT Node Security [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4343

Solving Quadratic Equations via Amplitude-based Nonconvex Optimization


In many signal processing tasks, one seeks to recover an r- column matrix object X ∈ Cn×r from a set of nonnegative quadratic measurements up to orthonormal transforms. Example applications include coherence retrieval in optical imaging and co- variance sketching for high-dimensional streaming data. To this end, efficient nonconvex optimization methods are quite appealing, due to their computational efficiency and scalability to large-scale problems.

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Authors:
Vincent Monardo, Yuanxin Li and Yuejie Chi
Submitted On:
10 May 2019 - 8:03am
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Poster for "Solving Quadratic Equations via Amplitude-based Nonconvex Optimization"

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[1] Vincent Monardo, Yuanxin Li and Yuejie Chi, "Solving Quadratic Equations via Amplitude-based Nonconvex Optimization", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4316. Accessed: Aug. 18, 2019.
@article{4316-19,
url = {http://sigport.org/4316},
author = {Vincent Monardo; Yuanxin Li and Yuejie Chi },
publisher = {IEEE SigPort},
title = {Solving Quadratic Equations via Amplitude-based Nonconvex Optimization},
year = {2019} }
TY - EJOUR
T1 - Solving Quadratic Equations via Amplitude-based Nonconvex Optimization
AU - Vincent Monardo; Yuanxin Li and Yuejie Chi
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4316
ER -
Vincent Monardo, Yuanxin Li and Yuejie Chi. (2019). Solving Quadratic Equations via Amplitude-based Nonconvex Optimization. IEEE SigPort. http://sigport.org/4316
Vincent Monardo, Yuanxin Li and Yuejie Chi, 2019. Solving Quadratic Equations via Amplitude-based Nonconvex Optimization. Available at: http://sigport.org/4316.
Vincent Monardo, Yuanxin Li and Yuejie Chi. (2019). "Solving Quadratic Equations via Amplitude-based Nonconvex Optimization." Web.
1. Vincent Monardo, Yuanxin Li and Yuejie Chi. Solving Quadratic Equations via Amplitude-based Nonconvex Optimization [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4316

Making Decisions with Shuffled Bits

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Authors:
Stefano Marano, Peter Willett
Submitted On:
10 May 2019 - 3:34am
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[1] Stefano Marano, Peter Willett, "Making Decisions with Shuffled Bits", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4282. Accessed: Aug. 18, 2019.
@article{4282-19,
url = {http://sigport.org/4282},
author = {Stefano Marano; Peter Willett },
publisher = {IEEE SigPort},
title = {Making Decisions with Shuffled Bits},
year = {2019} }
TY - EJOUR
T1 - Making Decisions with Shuffled Bits
AU - Stefano Marano; Peter Willett
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4282
ER -
Stefano Marano, Peter Willett. (2019). Making Decisions with Shuffled Bits. IEEE SigPort. http://sigport.org/4282
Stefano Marano, Peter Willett, 2019. Making Decisions with Shuffled Bits. Available at: http://sigport.org/4282.
Stefano Marano, Peter Willett. (2019). "Making Decisions with Shuffled Bits." Web.
1. Stefano Marano, Peter Willett. Making Decisions with Shuffled Bits [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4282

A Variational Adaptive Population Importance Sampler

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Authors:
Yousef El-Laham, Petar Djuric, Monica Bugallo
Submitted On:
9 May 2019 - 1:33pm
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[1] Yousef El-Laham, Petar Djuric, Monica Bugallo, "A Variational Adaptive Population Importance Sampler", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4227. Accessed: Aug. 18, 2019.
@article{4227-19,
url = {http://sigport.org/4227},
author = {Yousef El-Laham; Petar Djuric; Monica Bugallo },
publisher = {IEEE SigPort},
title = {A Variational Adaptive Population Importance Sampler},
year = {2019} }
TY - EJOUR
T1 - A Variational Adaptive Population Importance Sampler
AU - Yousef El-Laham; Petar Djuric; Monica Bugallo
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4227
ER -
Yousef El-Laham, Petar Djuric, Monica Bugallo. (2019). A Variational Adaptive Population Importance Sampler. IEEE SigPort. http://sigport.org/4227
Yousef El-Laham, Petar Djuric, Monica Bugallo, 2019. A Variational Adaptive Population Importance Sampler. Available at: http://sigport.org/4227.
Yousef El-Laham, Petar Djuric, Monica Bugallo. (2019). "A Variational Adaptive Population Importance Sampler." Web.
1. Yousef El-Laham, Petar Djuric, Monica Bugallo. A Variational Adaptive Population Importance Sampler [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4227

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