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Signal Processing Theory and Methods

Rumor Source Detection: A Probabilistic Perspective

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Authors:
Ting-Han Fan, I-Hsiang Wang
Submitted On:
12 April 2018 - 11:31pm
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ICASSP18_RSD_poster.pdf

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[1] Ting-Han Fan, I-Hsiang Wang, "Rumor Source Detection: A Probabilistic Perspective", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2570. Accessed: Dec. 12, 2018.
@article{2570-18,
url = {http://sigport.org/2570},
author = {Ting-Han Fan; I-Hsiang Wang },
publisher = {IEEE SigPort},
title = {Rumor Source Detection: A Probabilistic Perspective},
year = {2018} }
TY - EJOUR
T1 - Rumor Source Detection: A Probabilistic Perspective
AU - Ting-Han Fan; I-Hsiang Wang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2570
ER -
Ting-Han Fan, I-Hsiang Wang. (2018). Rumor Source Detection: A Probabilistic Perspective. IEEE SigPort. http://sigport.org/2570
Ting-Han Fan, I-Hsiang Wang, 2018. Rumor Source Detection: A Probabilistic Perspective. Available at: http://sigport.org/2570.
Ting-Han Fan, I-Hsiang Wang. (2018). "Rumor Source Detection: A Probabilistic Perspective." Web.
1. Ting-Han Fan, I-Hsiang Wang. Rumor Source Detection: A Probabilistic Perspective [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2570

UNEQUAL ERROR PROTECTION QUERYING POLICIES FOR THE NOISY 20 QUESTIONS PROBLEM


We propose a non-adaptive unequal error protection (UEP) querying policy based on superposition coding for the noisy 20 questions problem.
In this problem, a player wishes to successively refine an estimate of the value of a continuous random variable by posing binary queries and receiving noisy responses.
When the queries are designed non-adaptively as a single block and the noisy responses are modeled as the outputs of a binary symmetric channel the 20 questions problem can be mapped to an equivalent problem of channel coding with UEP.

poster.pdf

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Authors:
Brian Sadler, Lizhong Zheng, Alfred Hero
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12 April 2018 - 10:07pm
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poster.pdf

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[1] Brian Sadler, Lizhong Zheng, Alfred Hero, "UNEQUAL ERROR PROTECTION QUERYING POLICIES FOR THE NOISY 20 QUESTIONS PROBLEM", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2555. Accessed: Dec. 12, 2018.
@article{2555-18,
url = {http://sigport.org/2555},
author = {Brian Sadler; Lizhong Zheng; Alfred Hero },
publisher = {IEEE SigPort},
title = {UNEQUAL ERROR PROTECTION QUERYING POLICIES FOR THE NOISY 20 QUESTIONS PROBLEM},
year = {2018} }
TY - EJOUR
T1 - UNEQUAL ERROR PROTECTION QUERYING POLICIES FOR THE NOISY 20 QUESTIONS PROBLEM
AU - Brian Sadler; Lizhong Zheng; Alfred Hero
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2555
ER -
Brian Sadler, Lizhong Zheng, Alfred Hero. (2018). UNEQUAL ERROR PROTECTION QUERYING POLICIES FOR THE NOISY 20 QUESTIONS PROBLEM. IEEE SigPort. http://sigport.org/2555
Brian Sadler, Lizhong Zheng, Alfred Hero, 2018. UNEQUAL ERROR PROTECTION QUERYING POLICIES FOR THE NOISY 20 QUESTIONS PROBLEM. Available at: http://sigport.org/2555.
Brian Sadler, Lizhong Zheng, Alfred Hero. (2018). "UNEQUAL ERROR PROTECTION QUERYING POLICIES FOR THE NOISY 20 QUESTIONS PROBLEM." Web.
1. Brian Sadler, Lizhong Zheng, Alfred Hero. UNEQUAL ERROR PROTECTION QUERYING POLICIES FOR THE NOISY 20 QUESTIONS PROBLEM [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2555

RECOVERING SIGNALS FROM THEIR FROG TRACE

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Authors:
Tamir Bendory, Dan Edidin, Yonina Eldar
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12 April 2018 - 2:12pm
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FROG Poster v2.pdf

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[1] Tamir Bendory, Dan Edidin, Yonina Eldar , "RECOVERING SIGNALS FROM THEIR FROG TRACE", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2465. Accessed: Dec. 12, 2018.
@article{2465-18,
url = {http://sigport.org/2465},
author = {Tamir Bendory; Dan Edidin; Yonina Eldar },
publisher = {IEEE SigPort},
title = {RECOVERING SIGNALS FROM THEIR FROG TRACE},
year = {2018} }
TY - EJOUR
T1 - RECOVERING SIGNALS FROM THEIR FROG TRACE
AU - Tamir Bendory; Dan Edidin; Yonina Eldar
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2465
ER -
Tamir Bendory, Dan Edidin, Yonina Eldar . (2018). RECOVERING SIGNALS FROM THEIR FROG TRACE. IEEE SigPort. http://sigport.org/2465
Tamir Bendory, Dan Edidin, Yonina Eldar , 2018. RECOVERING SIGNALS FROM THEIR FROG TRACE. Available at: http://sigport.org/2465.
Tamir Bendory, Dan Edidin, Yonina Eldar . (2018). "RECOVERING SIGNALS FROM THEIR FROG TRACE." Web.
1. Tamir Bendory, Dan Edidin, Yonina Eldar . RECOVERING SIGNALS FROM THEIR FROG TRACE [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2465

ILAPF: INCREMENTAL LEARNING ASSISTED PARTICLE FILTERING

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12 April 2018 - 12:37pm
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ILAPF_Poster.pdf

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[1] , "ILAPF: INCREMENTAL LEARNING ASSISTED PARTICLE FILTERING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2435. Accessed: Dec. 12, 2018.
@article{2435-18,
url = {http://sigport.org/2435},
author = { },
publisher = {IEEE SigPort},
title = {ILAPF: INCREMENTAL LEARNING ASSISTED PARTICLE FILTERING},
year = {2018} }
TY - EJOUR
T1 - ILAPF: INCREMENTAL LEARNING ASSISTED PARTICLE FILTERING
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2435
ER -
. (2018). ILAPF: INCREMENTAL LEARNING ASSISTED PARTICLE FILTERING. IEEE SigPort. http://sigport.org/2435
, 2018. ILAPF: INCREMENTAL LEARNING ASSISTED PARTICLE FILTERING. Available at: http://sigport.org/2435.
. (2018). "ILAPF: INCREMENTAL LEARNING ASSISTED PARTICLE FILTERING." Web.
1. . ILAPF: INCREMENTAL LEARNING ASSISTED PARTICLE FILTERING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2435

ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY


Random sample consensus (RANSAC) is a popular paradigm for parameter estimation with outlier detection, which plays an essential role in 3D robot vision, especially for LiDAR odometry. The success of RANSAC strongly depends on the probability of selecting a subset of pure inliers, which sets barriers to robust and fast parameter estimation. Although significant efforts have been made to improve RANSAC in various scenarios, its strong dependency on inlier selection is still a problem.

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Authors:
Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin
Submitted On:
12 April 2018 - 11:26am
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[1] Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin, "ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2393. Accessed: Dec. 12, 2018.
@article{2393-18,
url = {http://sigport.org/2393},
author = {Hui Cheng; Yongheng Hu; Chongyu Chen; and Liang Lin },
publisher = {IEEE SigPort},
title = {ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY},
year = {2018} }
TY - EJOUR
T1 - ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY
AU - Hui Cheng; Yongheng Hu; Chongyu Chen; and Liang Lin
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2393
ER -
Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin. (2018). ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY. IEEE SigPort. http://sigport.org/2393
Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin, 2018. ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY. Available at: http://sigport.org/2393.
Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin. (2018). "ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY." Web.
1. Hui Cheng, Yongheng Hu, Chongyu Chen, and Liang Lin. ROBUST OBJECT-AWARE SAMPLE CONSENSUS WITH APPLICATION TO LIDAR ODOMETRY [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2393

Outlier-Robust Matrix Completion via lp-Minimization


Matrix completion refers to the recovery of a low‐rank matrix from only a subset of its possibly noisy entries, and has a variety of important applications such as collaborative filtering, image inpainting and restoration, system identification, node localization and genotype imputation. It is because many real-world signals can be approximated by a matrix whose rank is much smaller than the row and column numbers. Most techniques for matrix completion in the literature assume Gaussian noise and thus they are not robust to outliers.

rmp.pdf

PDF icon rmp.pdf (248 downloads)

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Authors:
Wen-Jun Zeng, Hing Cheung So
Submitted On:
2 March 2018 - 1:57am
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rmp.pdf

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[1] Wen-Jun Zeng, Hing Cheung So, "Outlier-Robust Matrix Completion via lp-Minimization", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2373. Accessed: Dec. 12, 2018.
@article{2373-18,
url = {http://sigport.org/2373},
author = {Wen-Jun Zeng; Hing Cheung So },
publisher = {IEEE SigPort},
title = {Outlier-Robust Matrix Completion via lp-Minimization},
year = {2018} }
TY - EJOUR
T1 - Outlier-Robust Matrix Completion via lp-Minimization
AU - Wen-Jun Zeng; Hing Cheung So
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2373
ER -
Wen-Jun Zeng, Hing Cheung So. (2018). Outlier-Robust Matrix Completion via lp-Minimization. IEEE SigPort. http://sigport.org/2373
Wen-Jun Zeng, Hing Cheung So, 2018. Outlier-Robust Matrix Completion via lp-Minimization. Available at: http://sigport.org/2373.
Wen-Jun Zeng, Hing Cheung So. (2018). "Outlier-Robust Matrix Completion via lp-Minimization." Web.
1. Wen-Jun Zeng, Hing Cheung So. Outlier-Robust Matrix Completion via lp-Minimization [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2373

Multiband TDOA Estimation from Sub-Nyquist Samples with Distributed Sensing Nodes

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Authors:
Anastasia Lavrenko, Florian Roemer, Giovanni Del Galdo, Reiner Thomä
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20 November 2017 - 9:21am
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GlobalSIP_2017_presentation.pdf

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[1] Anastasia Lavrenko, Florian Roemer, Giovanni Del Galdo, Reiner Thomä, "Multiband TDOA Estimation from Sub-Nyquist Samples with Distributed Sensing Nodes", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2366. Accessed: Dec. 12, 2018.
@article{2366-17,
url = {http://sigport.org/2366},
author = {Anastasia Lavrenko; Florian Roemer; Giovanni Del Galdo; Reiner Thomä },
publisher = {IEEE SigPort},
title = {Multiband TDOA Estimation from Sub-Nyquist Samples with Distributed Sensing Nodes},
year = {2017} }
TY - EJOUR
T1 - Multiband TDOA Estimation from Sub-Nyquist Samples with Distributed Sensing Nodes
AU - Anastasia Lavrenko; Florian Roemer; Giovanni Del Galdo; Reiner Thomä
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2366
ER -
Anastasia Lavrenko, Florian Roemer, Giovanni Del Galdo, Reiner Thomä. (2017). Multiband TDOA Estimation from Sub-Nyquist Samples with Distributed Sensing Nodes. IEEE SigPort. http://sigport.org/2366
Anastasia Lavrenko, Florian Roemer, Giovanni Del Galdo, Reiner Thomä, 2017. Multiband TDOA Estimation from Sub-Nyquist Samples with Distributed Sensing Nodes. Available at: http://sigport.org/2366.
Anastasia Lavrenko, Florian Roemer, Giovanni Del Galdo, Reiner Thomä. (2017). "Multiband TDOA Estimation from Sub-Nyquist Samples with Distributed Sensing Nodes." Web.
1. Anastasia Lavrenko, Florian Roemer, Giovanni Del Galdo, Reiner Thomä. Multiband TDOA Estimation from Sub-Nyquist Samples with Distributed Sensing Nodes [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2366

1161: Image Super-Resolution Using Nonlocally Centralized Sparse Representation and Fields of Experts Priors

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Authors:
Wei zhou, Zhemin Duan
Submitted On:
10 November 2017 - 1:17am
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GlobalSIP_poster - zhangxiu.pdf

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[1] Wei zhou, Zhemin Duan, "1161: Image Super-Resolution Using Nonlocally Centralized Sparse Representation and Fields of Experts Priors", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2284. Accessed: Dec. 12, 2018.
@article{2284-17,
url = {http://sigport.org/2284},
author = {Wei zhou; Zhemin Duan },
publisher = {IEEE SigPort},
title = {1161: Image Super-Resolution Using Nonlocally Centralized Sparse Representation and Fields of Experts Priors},
year = {2017} }
TY - EJOUR
T1 - 1161: Image Super-Resolution Using Nonlocally Centralized Sparse Representation and Fields of Experts Priors
AU - Wei zhou; Zhemin Duan
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2284
ER -
Wei zhou, Zhemin Duan. (2017). 1161: Image Super-Resolution Using Nonlocally Centralized Sparse Representation and Fields of Experts Priors. IEEE SigPort. http://sigport.org/2284
Wei zhou, Zhemin Duan, 2017. 1161: Image Super-Resolution Using Nonlocally Centralized Sparse Representation and Fields of Experts Priors. Available at: http://sigport.org/2284.
Wei zhou, Zhemin Duan. (2017). "1161: Image Super-Resolution Using Nonlocally Centralized Sparse Representation and Fields of Experts Priors." Web.
1. Wei zhou, Zhemin Duan. 1161: Image Super-Resolution Using Nonlocally Centralized Sparse Representation and Fields of Experts Priors [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2284

TIME SAMPLES SELECTION IN SPIRAL ACQUISITION FOR SPARSE MAGNETIC RESONANCE SPECTROSCOPIC IMAGING

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Authors:
Fabien Millioz, Maglie Viallon, Remy Prost, Helene Ratiney
Submitted On:
12 September 2017 - 10:28am
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posterICIP2017vf.pdf

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[1] Fabien Millioz, Maglie Viallon, Remy Prost, Helene Ratiney, "TIME SAMPLES SELECTION IN SPIRAL ACQUISITION FOR SPARSE MAGNETIC RESONANCE SPECTROSCOPIC IMAGING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1939. Accessed: Dec. 12, 2018.
@article{1939-17,
url = {http://sigport.org/1939},
author = {Fabien Millioz; Maglie Viallon; Remy Prost; Helene Ratiney },
publisher = {IEEE SigPort},
title = {TIME SAMPLES SELECTION IN SPIRAL ACQUISITION FOR SPARSE MAGNETIC RESONANCE SPECTROSCOPIC IMAGING},
year = {2017} }
TY - EJOUR
T1 - TIME SAMPLES SELECTION IN SPIRAL ACQUISITION FOR SPARSE MAGNETIC RESONANCE SPECTROSCOPIC IMAGING
AU - Fabien Millioz; Maglie Viallon; Remy Prost; Helene Ratiney
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1939
ER -
Fabien Millioz, Maglie Viallon, Remy Prost, Helene Ratiney. (2017). TIME SAMPLES SELECTION IN SPIRAL ACQUISITION FOR SPARSE MAGNETIC RESONANCE SPECTROSCOPIC IMAGING. IEEE SigPort. http://sigport.org/1939
Fabien Millioz, Maglie Viallon, Remy Prost, Helene Ratiney, 2017. TIME SAMPLES SELECTION IN SPIRAL ACQUISITION FOR SPARSE MAGNETIC RESONANCE SPECTROSCOPIC IMAGING. Available at: http://sigport.org/1939.
Fabien Millioz, Maglie Viallon, Remy Prost, Helene Ratiney. (2017). "TIME SAMPLES SELECTION IN SPIRAL ACQUISITION FOR SPARSE MAGNETIC RESONANCE SPECTROSCOPIC IMAGING." Web.
1. Fabien Millioz, Maglie Viallon, Remy Prost, Helene Ratiney. TIME SAMPLES SELECTION IN SPIRAL ACQUISITION FOR SPARSE MAGNETIC RESONANCE SPECTROSCOPIC IMAGING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1939

Phase Retrieval via Coordinate Descent


Phase retrieval refers to recovery of a signal-of-interest given only the intensity measurement samples and has wide applicability including important areas of astronomy, computational biology, crystallography, digital communications, electron microscopy, neutron radiography and optical imaging. The classical problem formulation is to restore the time-domain signal from its power spectrum observations, although the Fourier transform can be generalized to any linear mappings.

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28 June 2017 - 11:19pm
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[1] , "Phase Retrieval via Coordinate Descent", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1799. Accessed: Dec. 12, 2018.
@article{1799-17,
url = {http://sigport.org/1799},
author = { },
publisher = {IEEE SigPort},
title = {Phase Retrieval via Coordinate Descent},
year = {2017} }
TY - EJOUR
T1 - Phase Retrieval via Coordinate Descent
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1799
ER -
. (2017). Phase Retrieval via Coordinate Descent. IEEE SigPort. http://sigport.org/1799
, 2017. Phase Retrieval via Coordinate Descent. Available at: http://sigport.org/1799.
. (2017). "Phase Retrieval via Coordinate Descent." Web.
1. . Phase Retrieval via Coordinate Descent [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1799

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