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Emerging: Big Data

Signal Processing on Graphs: Performance of Graph Structure Estimation

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Authors:
Jonathan Mei, José M F Moura
Submitted On:
15 March 2016 - 4:02pm
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icassp_jmei2016.pptx

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[1] Jonathan Mei, José M F Moura, "Signal Processing on Graphs: Performance of Graph Structure Estimation", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/696. Accessed: Oct. 19, 2017.
@article{696-16,
url = {http://sigport.org/696},
author = {Jonathan Mei; José M F Moura },
publisher = {IEEE SigPort},
title = {Signal Processing on Graphs: Performance of Graph Structure Estimation},
year = {2016} }
TY - EJOUR
T1 - Signal Processing on Graphs: Performance of Graph Structure Estimation
AU - Jonathan Mei; José M F Moura
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/696
ER -
Jonathan Mei, José M F Moura. (2016). Signal Processing on Graphs: Performance of Graph Structure Estimation. IEEE SigPort. http://sigport.org/696
Jonathan Mei, José M F Moura, 2016. Signal Processing on Graphs: Performance of Graph Structure Estimation. Available at: http://sigport.org/696.
Jonathan Mei, José M F Moura. (2016). "Signal Processing on Graphs: Performance of Graph Structure Estimation." Web.
1. Jonathan Mei, José M F Moura. Signal Processing on Graphs: Performance of Graph Structure Estimation [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/696

SmartRoadSense - A collaborative project for monitoring road surface conditions


SmartRoadSense is a collaborative project aimed at monitoring road surface conditions exploiting the sensors, i.e., accelerometers and GPS, commonly embedded in most mobile devices. Given a smartphone connected to the cabin of a car travelling on a road, the SmartRoadSense app analyzes the accelerometer signals and extracts a roughness index (based on a linear predictive coding analysis) characterizing the quality of the road.

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Authors:
Emanuele Lattanzi, Valerio Freschi, Alessandro Bogliolo
Submitted On:
5 April 2016 - 5:31am
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SmartRoadSense.pdf

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[1] Emanuele Lattanzi, Valerio Freschi, Alessandro Bogliolo, "SmartRoadSense - A collaborative project for monitoring road surface conditions", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/677. Accessed: Oct. 19, 2017.
@article{677-16,
url = {http://sigport.org/677},
author = {Emanuele Lattanzi; Valerio Freschi; Alessandro Bogliolo },
publisher = {IEEE SigPort},
title = {SmartRoadSense - A collaborative project for monitoring road surface conditions},
year = {2016} }
TY - EJOUR
T1 - SmartRoadSense - A collaborative project for monitoring road surface conditions
AU - Emanuele Lattanzi; Valerio Freschi; Alessandro Bogliolo
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/677
ER -
Emanuele Lattanzi, Valerio Freschi, Alessandro Bogliolo. (2016). SmartRoadSense - A collaborative project for monitoring road surface conditions. IEEE SigPort. http://sigport.org/677
Emanuele Lattanzi, Valerio Freschi, Alessandro Bogliolo, 2016. SmartRoadSense - A collaborative project for monitoring road surface conditions. Available at: http://sigport.org/677.
Emanuele Lattanzi, Valerio Freschi, Alessandro Bogliolo. (2016). "SmartRoadSense - A collaborative project for monitoring road surface conditions." Web.
1. Emanuele Lattanzi, Valerio Freschi, Alessandro Bogliolo. SmartRoadSense - A collaborative project for monitoring road surface conditions [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/677

Non-monotone Quadratic Potential Games with single Quadratic constraints


We consider the problem of solving a quadratic potential game with single quadratic constraints, under no monotonicity condition of the game, nor convexity in any of the player's problem. We show existence of Nash equilibria (NE) in the game, and propose a framework to calculate Pareto efficient solutions. Regarding the corresponding non-convex potential function, we show that strong duality holds with its corresponding dual problem, give existence results of solutions and present conditions for global optimality. Finally, we propose a centralized method to solve the potential problem, and a distributed version for compact constraints. We also present simulations showing convergence behavior of the proposed distributed algorithm.

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Authors:
Santiago Zazo, Sergio Valcarcel Macua
Submitted On:
29 March 2016 - 9:57am
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quadratic_poster.pdf

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[1] Santiago Zazo, Sergio Valcarcel Macua, "Non-monotone Quadratic Potential Games with single Quadratic constraints", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/632. Accessed: Oct. 19, 2017.
@article{632-16,
url = {http://sigport.org/632},
author = {Santiago Zazo; Sergio Valcarcel Macua },
publisher = {IEEE SigPort},
title = {Non-monotone Quadratic Potential Games with single Quadratic constraints},
year = {2016} }
TY - EJOUR
T1 - Non-monotone Quadratic Potential Games with single Quadratic constraints
AU - Santiago Zazo; Sergio Valcarcel Macua
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/632
ER -
Santiago Zazo, Sergio Valcarcel Macua. (2016). Non-monotone Quadratic Potential Games with single Quadratic constraints. IEEE SigPort. http://sigport.org/632
Santiago Zazo, Sergio Valcarcel Macua, 2016. Non-monotone Quadratic Potential Games with single Quadratic constraints. Available at: http://sigport.org/632.
Santiago Zazo, Sergio Valcarcel Macua. (2016). "Non-monotone Quadratic Potential Games with single Quadratic constraints." Web.
1. Santiago Zazo, Sergio Valcarcel Macua. Non-monotone Quadratic Potential Games with single Quadratic constraints [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/632

Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP


In the 1960s, Marshall McLuhan published the book entitled, The Extensions of Man focusing primarily on television, an electronic media as being the outward extension of human nervous system, which from contemporary interpretation marks the previous stage of Big Data.

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Authors:
Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia
Submitted On:
23 February 2016 - 1:44pm
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GlobalSIPS 2015 Panel Discussion Presentation.pdf

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[1] Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia, "Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/569. Accessed: Oct. 19, 2017.
@article{569-15,
url = {http://sigport.org/569},
author = {Lee Barford; Paul Blinzer; Joe Cavallaro; Hong; Jiang; Nick Moore; Yinglong Xia },
publisher = {IEEE SigPort},
title = {Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP},
year = {2015} }
TY - EJOUR
T1 - Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP
AU - Lee Barford; Paul Blinzer; Joe Cavallaro; Hong; Jiang; Nick Moore; Yinglong Xia
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/569
ER -
Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia. (2015). Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP. IEEE SigPort. http://sigport.org/569
Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia, 2015. Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP. Available at: http://sigport.org/569.
Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia. (2015). "Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP." Web.
1. Lee Barford, Paul Blinzer, Joe Cavallaro, Hong, Jiang, Nick Moore, Yinglong Xia. Panel Discussion: Algorithms vs. Architectures: Opportunities and Challenges in Multicore/GPU DSP [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/569

Models for Spectral Clustering and Their Applications


Microarray Spectral Clustering.

Ph.D. Thesis by Donald McCuan (advisor Andrew Knyazev), Department of Mathematical and Statistical Sciences, University of Colorado Denver, 2012, originally posted at http://math.ucdenver.edu/theses/McCuan_PhdThesis.pdf (499 downloads)

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Donald Donald
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23 February 2016 - 1:44pm
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McCuan_PhdThesis.pdf

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[1] Donald Donald, "Models for Spectral Clustering and Their Applications", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/564. Accessed: Oct. 19, 2017.
@article{564-15,
url = {http://sigport.org/564},
author = {Donald Donald },
publisher = {IEEE SigPort},
title = {Models for Spectral Clustering and Their Applications},
year = {2015} }
TY - EJOUR
T1 - Models for Spectral Clustering and Their Applications
AU - Donald Donald
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/564
ER -
Donald Donald. (2015). Models for Spectral Clustering and Their Applications. IEEE SigPort. http://sigport.org/564
Donald Donald, 2015. Models for Spectral Clustering and Their Applications. Available at: http://sigport.org/564.
Donald Donald. (2015). "Models for Spectral Clustering and Their Applications." Web.
1. Donald Donald. Models for Spectral Clustering and Their Applications [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/564

Multigrid Eigensolvers for Image Segmentation


Spectral Image Segmentation

Presentation at LANL and UC Davis, 2009. Originally posted at http://math.ucdenver.edu/~aknyazev/research/conf/

LANL09.ppt

Office presentation icon LANL09.ppt (272 downloads)

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23 February 2016 - 1:44pm
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LANL09.ppt

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[1] , "Multigrid Eigensolvers for Image Segmentation", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/562. Accessed: Oct. 19, 2017.
@article{562-15,
url = {http://sigport.org/562},
author = { },
publisher = {IEEE SigPort},
title = {Multigrid Eigensolvers for Image Segmentation},
year = {2015} }
TY - EJOUR
T1 - Multigrid Eigensolvers for Image Segmentation
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/562
ER -
. (2015). Multigrid Eigensolvers for Image Segmentation. IEEE SigPort. http://sigport.org/562
, 2015. Multigrid Eigensolvers for Image Segmentation. Available at: http://sigport.org/562.
. (2015). "Multigrid Eigensolvers for Image Segmentation." Web.
1. . Multigrid Eigensolvers for Image Segmentation [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/562

Novel data clustering for microarrays and image segmentation


Spectral Clustering Eigenvalue Problem

We develop novel algorithms and software on parallel computers for data clustering of large datasets. We are interested in applying our approach, e.g., for analysis of large datasets of microarrays or tiling arrays in molecular biology and for segmentation of high resolution images.

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23 February 2016 - 1:44pm
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camready-1031.ppt

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[1] , "Novel data clustering for microarrays and image segmentation", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/561. Accessed: Oct. 19, 2017.
@article{561-15,
url = {http://sigport.org/561},
author = { },
publisher = {IEEE SigPort},
title = {Novel data clustering for microarrays and image segmentation},
year = {2015} }
TY - EJOUR
T1 - Novel data clustering for microarrays and image segmentation
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/561
ER -
. (2015). Novel data clustering for microarrays and image segmentation. IEEE SigPort. http://sigport.org/561
, 2015. Novel data clustering for microarrays and image segmentation. Available at: http://sigport.org/561.
. (2015). "Novel data clustering for microarrays and image segmentation." Web.
1. . Novel data clustering for microarrays and image segmentation [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/561

Social Media Analytics for Crisis Response


Crises or large-scale emergencies such as earthquakes and hurricanes cause massive damage to lives and property. Crisis response is an essential task to mitigate the impact of a crisis. An effective response to a crisis necessitates information gathering and analysis. Traditionally, this process has been restricted to the information collected by first responders on the ground in the affected region or by official agencies such as local governments involved in the response.

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23 February 2016 - 1:44pm
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Shamanth_thesis.pdf

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[1] , "Social Media Analytics for Crisis Response", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/541. Accessed: Oct. 19, 2017.
@article{541-15,
url = {http://sigport.org/541},
author = { },
publisher = {IEEE SigPort},
title = {Social Media Analytics for Crisis Response},
year = {2015} }
TY - EJOUR
T1 - Social Media Analytics for Crisis Response
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/541
ER -
. (2015). Social Media Analytics for Crisis Response. IEEE SigPort. http://sigport.org/541
, 2015. Social Media Analytics for Crisis Response. Available at: http://sigport.org/541.
. (2015). "Social Media Analytics for Crisis Response." Web.
1. . Social Media Analytics for Crisis Response [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/541

Social Media Analytics for Crisis Response


Crises and situations of mass emergency such as earthquakes and hurricanes cause massive damage to lives and property. Crisis response is an essential task to mitigate the impact of a crisis. An effective response to a crisis necessitates information gathering and analysis. Traditionally this process has been restricted to the information collected by first responders on the ground in the affected region or official agencies such as local governments involved in the response.

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23 February 2016 - 1:44pm
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Shamanth_Kumar_Thesis_slides_2015.pptx

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[1] , "Social Media Analytics for Crisis Response", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/539. Accessed: Oct. 19, 2017.
@article{539-15,
url = {http://sigport.org/539},
author = { },
publisher = {IEEE SigPort},
title = {Social Media Analytics for Crisis Response},
year = {2015} }
TY - EJOUR
T1 - Social Media Analytics for Crisis Response
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/539
ER -
. (2015). Social Media Analytics for Crisis Response. IEEE SigPort. http://sigport.org/539
, 2015. Social Media Analytics for Crisis Response. Available at: http://sigport.org/539.
. (2015). "Social Media Analytics for Crisis Response." Web.
1. . Social Media Analytics for Crisis Response [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/539

Edge-enhancing filters with negative weights


Edge-enhanced eigenvectors of the Laplacian with a negative weight

In [doi{10.1109/ICMEW.2014.6890711}], a~graph-based filtering of noisy images is performed by directly computing a projection of the image to be filtered onto a lower dimensional Krylov subspace of the graph Laplacian, constructed using non-negative graph weights determined by distances between image data corresponding to image pixels. We extend the construction of the graph Laplacian to the case, where some graph weights can be negative.

KGlobalSIP.pdf

PDF icon KGlobalSIP.pdf (286 downloads)

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23 February 2016 - 1:44pm
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KGlobalSIP.pdf

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[1] , "Edge-enhancing filters with negative weights", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/503. Accessed: Oct. 19, 2017.
@article{503-15,
url = {http://sigport.org/503},
author = { },
publisher = {IEEE SigPort},
title = {Edge-enhancing filters with negative weights},
year = {2015} }
TY - EJOUR
T1 - Edge-enhancing filters with negative weights
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/503
ER -
. (2015). Edge-enhancing filters with negative weights. IEEE SigPort. http://sigport.org/503
, 2015. Edge-enhancing filters with negative weights. Available at: http://sigport.org/503.
. (2015). "Edge-enhancing filters with negative weights." Web.
1. . Edge-enhancing filters with negative weights [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/503

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