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ICASSP 2020

ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The ICASSP 2020 conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world. Visit website.

Stability of Graph Neural Networks to Relative Perturbations


Graph neural networks (GNNs), consisting of a cascade of layers applying a graph convolution followed by a pointwise nonlinearity, have become a powerful architecture to process signals supported on graphs. Graph convolutions (and thus, GNNs), rely heavily on knowledge of the graph for operation. However, in many practical cases the graph shift operator (GSO) is not known and needs to be estimated, or might change from training time to testing time.

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Authors:
Fernando Gama, Joan Bruna, Alejandro Ribeiro
Submitted On:
13 May 2020 - 5:59pm
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[1] Fernando Gama, Joan Bruna, Alejandro Ribeiro, "Stability of Graph Neural Networks to Relative Perturbations", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5159. Accessed: Aug. 06, 2020.
@article{5159-20,
url = {http://sigport.org/5159},
author = {Fernando Gama; Joan Bruna; Alejandro Ribeiro },
publisher = {IEEE SigPort},
title = {Stability of Graph Neural Networks to Relative Perturbations},
year = {2020} }
TY - EJOUR
T1 - Stability of Graph Neural Networks to Relative Perturbations
AU - Fernando Gama; Joan Bruna; Alejandro Ribeiro
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5159
ER -
Fernando Gama, Joan Bruna, Alejandro Ribeiro. (2020). Stability of Graph Neural Networks to Relative Perturbations. IEEE SigPort. http://sigport.org/5159
Fernando Gama, Joan Bruna, Alejandro Ribeiro, 2020. Stability of Graph Neural Networks to Relative Perturbations. Available at: http://sigport.org/5159.
Fernando Gama, Joan Bruna, Alejandro Ribeiro. (2020). "Stability of Graph Neural Networks to Relative Perturbations." Web.
1. Fernando Gama, Joan Bruna, Alejandro Ribeiro. Stability of Graph Neural Networks to Relative Perturbations [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5159

Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction


Deep neural networks (DNNs) are successful in applications with matching inference and training distributions. In realworld scenarios, DNNs have to cope with truly new data samples during inference, potentially coming from a shifted data distribution. This usually causes a drop in performance. Acoustic scene classification (ASC) with different recording devices is one of this situation. Furthermore, an imbalance in quality and amount of data recorded by different devices causes severe challenges. In this paper, we introduce two calibration methods to tackle these challenges.

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Authors:
Truc Nguyen, Franz Pernkopf, Michal Kosmider
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13 May 2020 - 5:52pm
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[1] Truc Nguyen, Franz Pernkopf, Michal Kosmider, "Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5158. Accessed: Aug. 06, 2020.
@article{5158-20,
url = {http://sigport.org/5158},
author = {Truc Nguyen; Franz Pernkopf; Michal Kosmider },
publisher = {IEEE SigPort},
title = {Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction},
year = {2020} }
TY - EJOUR
T1 - Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction
AU - Truc Nguyen; Franz Pernkopf; Michal Kosmider
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5158
ER -
Truc Nguyen, Franz Pernkopf, Michal Kosmider. (2020). Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction. IEEE SigPort. http://sigport.org/5158
Truc Nguyen, Franz Pernkopf, Michal Kosmider, 2020. Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction. Available at: http://sigport.org/5158.
Truc Nguyen, Franz Pernkopf, Michal Kosmider. (2020). "Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction." Web.
1. Truc Nguyen, Franz Pernkopf, Michal Kosmider. Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5158

COMPLEX PAIRWISE ACTIVITY ANALYSIS VIA INSTANCE LEVEL EVOLUTION REASONING


Video activity analysis systems are often trained on large datasets. Activities and events in the real-world do not occur in isolation, instead, they occur as interactions between related objects. This work introduces a novel method that jointly exploits relational information between pairs of objects and temporal dynamics of each object. The proposed method effectively leverages a new simple architecture that is flexible and easily trained to detect relational activities and events using small datasets (hundreds of samples).

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Authors:
Sudipta Paul, Carlos Torres, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury
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13 May 2020 - 5:43pm
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[1] Sudipta Paul, Carlos Torres, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury, "COMPLEX PAIRWISE ACTIVITY ANALYSIS VIA INSTANCE LEVEL EVOLUTION REASONING", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5157. Accessed: Aug. 06, 2020.
@article{5157-20,
url = {http://sigport.org/5157},
author = {Sudipta Paul; Carlos Torres; Shivkumar Chandrasekaran; Amit K. Roy-Chowdhury },
publisher = {IEEE SigPort},
title = {COMPLEX PAIRWISE ACTIVITY ANALYSIS VIA INSTANCE LEVEL EVOLUTION REASONING},
year = {2020} }
TY - EJOUR
T1 - COMPLEX PAIRWISE ACTIVITY ANALYSIS VIA INSTANCE LEVEL EVOLUTION REASONING
AU - Sudipta Paul; Carlos Torres; Shivkumar Chandrasekaran; Amit K. Roy-Chowdhury
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5157
ER -
Sudipta Paul, Carlos Torres, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury. (2020). COMPLEX PAIRWISE ACTIVITY ANALYSIS VIA INSTANCE LEVEL EVOLUTION REASONING. IEEE SigPort. http://sigport.org/5157
Sudipta Paul, Carlos Torres, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury, 2020. COMPLEX PAIRWISE ACTIVITY ANALYSIS VIA INSTANCE LEVEL EVOLUTION REASONING. Available at: http://sigport.org/5157.
Sudipta Paul, Carlos Torres, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury. (2020). "COMPLEX PAIRWISE ACTIVITY ANALYSIS VIA INSTANCE LEVEL EVOLUTION REASONING." Web.
1. Sudipta Paul, Carlos Torres, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury. COMPLEX PAIRWISE ACTIVITY ANALYSIS VIA INSTANCE LEVEL EVOLUTION REASONING [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5157

Secure Identification for Gaussian Channels


New applications in modern communications are demanding robust and ultra-reliable low latency information exchange such as machine-to-machine and human-to-machine communications. For many of these applications, the identification approach of Ahlswede and Dueck is much more efficient than the classical transmission scheme proposed by Shannon. Previous studies concentrate mainly on identification over discrete channels. We focus on Gaussian channels for their known practical relevance. We deal with secure identification over Gaussian channels.

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Authors:
Wafa Labidi, Christian Deppe, Holger Boche
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13 May 2020 - 5:43pm
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[1] Wafa Labidi, Christian Deppe, Holger Boche, "Secure Identification for Gaussian Channels", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5156. Accessed: Aug. 06, 2020.
@article{5156-20,
url = {http://sigport.org/5156},
author = {Wafa Labidi; Christian Deppe; Holger Boche },
publisher = {IEEE SigPort},
title = {Secure Identification for Gaussian Channels},
year = {2020} }
TY - EJOUR
T1 - Secure Identification for Gaussian Channels
AU - Wafa Labidi; Christian Deppe; Holger Boche
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5156
ER -
Wafa Labidi, Christian Deppe, Holger Boche. (2020). Secure Identification for Gaussian Channels. IEEE SigPort. http://sigport.org/5156
Wafa Labidi, Christian Deppe, Holger Boche, 2020. Secure Identification for Gaussian Channels. Available at: http://sigport.org/5156.
Wafa Labidi, Christian Deppe, Holger Boche. (2020). "Secure Identification for Gaussian Channels." Web.
1. Wafa Labidi, Christian Deppe, Holger Boche. Secure Identification for Gaussian Channels [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5156

ICASSP 2020 presentation slide of 'EXTRAPOLATED ALTERNATING ALGORITHMS FOR APPROXIMATE CANONICAL POLYADIC DECOMPOSITION'


Tensor decompositions have become a central tool in machine learning to extract interpretable patterns from multiway arrays of data. However, computing the approximate Canonical Polyadic Decomposition (aCPD), one of the most important tensor decomposition model, remains a challenge. In this work, we propose several algorithms based on extrapolation that improve over existing alternating methods for aCPD.

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Authors:
Andersen M. S. Ang, Jérémy Emile Cohen, Le Thi Khanh Hien, Nicolas Gillis
Submitted On:
13 May 2020 - 5:42pm
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[1] Andersen M. S. Ang, Jérémy Emile Cohen, Le Thi Khanh Hien, Nicolas Gillis, "ICASSP 2020 presentation slide of 'EXTRAPOLATED ALTERNATING ALGORITHMS FOR APPROXIMATE CANONICAL POLYADIC DECOMPOSITION'", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5155. Accessed: Aug. 06, 2020.
@article{5155-20,
url = {http://sigport.org/5155},
author = {Andersen M. S. Ang; Jérémy Emile Cohen; Le Thi Khanh Hien; Nicolas Gillis },
publisher = {IEEE SigPort},
title = {ICASSP 2020 presentation slide of 'EXTRAPOLATED ALTERNATING ALGORITHMS FOR APPROXIMATE CANONICAL POLYADIC DECOMPOSITION'},
year = {2020} }
TY - EJOUR
T1 - ICASSP 2020 presentation slide of 'EXTRAPOLATED ALTERNATING ALGORITHMS FOR APPROXIMATE CANONICAL POLYADIC DECOMPOSITION'
AU - Andersen M. S. Ang; Jérémy Emile Cohen; Le Thi Khanh Hien; Nicolas Gillis
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5155
ER -
Andersen M. S. Ang, Jérémy Emile Cohen, Le Thi Khanh Hien, Nicolas Gillis. (2020). ICASSP 2020 presentation slide of 'EXTRAPOLATED ALTERNATING ALGORITHMS FOR APPROXIMATE CANONICAL POLYADIC DECOMPOSITION'. IEEE SigPort. http://sigport.org/5155
Andersen M. S. Ang, Jérémy Emile Cohen, Le Thi Khanh Hien, Nicolas Gillis, 2020. ICASSP 2020 presentation slide of 'EXTRAPOLATED ALTERNATING ALGORITHMS FOR APPROXIMATE CANONICAL POLYADIC DECOMPOSITION'. Available at: http://sigport.org/5155.
Andersen M. S. Ang, Jérémy Emile Cohen, Le Thi Khanh Hien, Nicolas Gillis. (2020). "ICASSP 2020 presentation slide of 'EXTRAPOLATED ALTERNATING ALGORITHMS FOR APPROXIMATE CANONICAL POLYADIC DECOMPOSITION'." Web.
1. Andersen M. S. Ang, Jérémy Emile Cohen, Le Thi Khanh Hien, Nicolas Gillis. ICASSP 2020 presentation slide of 'EXTRAPOLATED ALTERNATING ALGORITHMS FOR APPROXIMATE CANONICAL POLYADIC DECOMPOSITION' [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5155

Secure Identification for Gaussian Channels


New applications in modern communications are demanding robust and ultra-reliable low latency information exchange such as machine-to-machine and human-to-machine communications. For many of these applications, the identification approach of Ahlswede and Dueck is much more efficient than the classical transmission scheme proposed by Shannon. Previous studies concentrate mainly on identification over discrete channels. We focus on Gaussian channels for their known practical relevance. We deal with secure identification over Gaussian channels.

Paper Details

Authors:
Wafa Labidi, Christian Deppe, Holger Boche
Submitted On:
13 May 2020 - 5:32pm
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[1] Wafa Labidi, Christian Deppe, Holger Boche, "Secure Identification for Gaussian Channels", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5154. Accessed: Aug. 06, 2020.
@article{5154-20,
url = {http://sigport.org/5154},
author = {Wafa Labidi; Christian Deppe; Holger Boche },
publisher = {IEEE SigPort},
title = {Secure Identification for Gaussian Channels},
year = {2020} }
TY - EJOUR
T1 - Secure Identification for Gaussian Channels
AU - Wafa Labidi; Christian Deppe; Holger Boche
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5154
ER -
Wafa Labidi, Christian Deppe, Holger Boche. (2020). Secure Identification for Gaussian Channels. IEEE SigPort. http://sigport.org/5154
Wafa Labidi, Christian Deppe, Holger Boche, 2020. Secure Identification for Gaussian Channels. Available at: http://sigport.org/5154.
Wafa Labidi, Christian Deppe, Holger Boche. (2020). "Secure Identification for Gaussian Channels." Web.
1. Wafa Labidi, Christian Deppe, Holger Boche. Secure Identification for Gaussian Channels [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5154

MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY


Multi-channel sparse blind deconvolution refers to the problem of learning an unknown filter by observing its circulant convolutions with multiple input signals that are sparse. It is challenging to learn the filter efficiently due to the bilinear structure of the observations with respect to the unknown filter and inputs, leading to global ambiguities of identification. We propose a novel approach based on nonconvex optimization over the sphere manifold by minimizing a smooth surrogate of the sparsity-promoting loss function.

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Authors:
Laixi Shi, Yuejie Chi
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13 May 2020 - 5:30pm
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[1] Laixi Shi, Yuejie Chi, "MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5153. Accessed: Aug. 06, 2020.
@article{5153-20,
url = {http://sigport.org/5153},
author = {Laixi Shi; Yuejie Chi },
publisher = {IEEE SigPort},
title = {MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY},
year = {2020} }
TY - EJOUR
T1 - MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY
AU - Laixi Shi; Yuejie Chi
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5153
ER -
Laixi Shi, Yuejie Chi. (2020). MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY. IEEE SigPort. http://sigport.org/5153
Laixi Shi, Yuejie Chi, 2020. MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY. Available at: http://sigport.org/5153.
Laixi Shi, Yuejie Chi. (2020). "MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY." Web.
1. Laixi Shi, Yuejie Chi. MANIFOLD GRADIENT DESCENT SOLVES MULTI-CHANNEL SPARSE BLIND DECONVOLUTION PROVABLY AND EFFICIENTLY [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5153

TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION


We propose a spiking neural network model that encodes information in the relative timing of individual neuron spikes and performs classification using the first output neuron to spike. This temporal coding scheme allows the supervised training of the network with backpropagation, using locally exact derivatives of the postsynaptic with respect to presynaptic spike times. The network uses a biologically-inspired alpha synaptic transfer function and trainable synchronisation pulses as temporal references. We successfully train the network on the MNIST dataset encoded in time.

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Authors:
Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala
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13 May 2020 - 5:28pm
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[1] Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala, "TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5151. Accessed: Aug. 06, 2020.
@article{5151-20,
url = {http://sigport.org/5151},
author = {Iulia M. Comsa; Krzysztof Potempa; Luca Versari; Thomas Fischbacher; Andrea Gesmundo; Jyrki Alakuijala },
publisher = {IEEE SigPort},
title = {TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION},
year = {2020} }
TY - EJOUR
T1 - TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION
AU - Iulia M. Comsa; Krzysztof Potempa; Luca Versari; Thomas Fischbacher; Andrea Gesmundo; Jyrki Alakuijala
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5151
ER -
Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala. (2020). TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION. IEEE SigPort. http://sigport.org/5151
Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala, 2020. TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION. Available at: http://sigport.org/5151.
Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala. (2020). "TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION." Web.
1. Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala. TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5151

TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION

Paper Details

Authors:
Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala
Submitted On:
13 May 2020 - 5:28pm
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[1] Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala, "TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5152. Accessed: Aug. 06, 2020.
@article{5152-20,
url = {http://sigport.org/5152},
author = {Iulia M. Comsa; Krzysztof Potempa; Luca Versari; Thomas Fischbacher; Andrea Gesmundo; Jyrki Alakuijala },
publisher = {IEEE SigPort},
title = {TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION},
year = {2020} }
TY - EJOUR
T1 - TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION
AU - Iulia M. Comsa; Krzysztof Potempa; Luca Versari; Thomas Fischbacher; Andrea Gesmundo; Jyrki Alakuijala
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5152
ER -
Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala. (2020). TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION. IEEE SigPort. http://sigport.org/5152
Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala, 2020. TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION. Available at: http://sigport.org/5152.
Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala. (2020). "TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION." Web.
1. Iulia M. Comsa, Krzysztof Potempa, Luca Versari, Thomas Fischbacher, Andrea Gesmundo, Jyrki Alakuijala. TEMPORAL CODING IN SPIKING NEURAL NETWORKS WITH ALPHA SYNAPTIC FUNCTION [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5152

Gaussian process imputation of multiple financial series


In Financial Signal Processing, multiple time series such as financial indicators, stock prices and exchange rates are strongly coupled due to their dependence on the latent state of the market and therefore they are required to be jointly analysed. We focus on learning the relationships among financial time series by modelling them through a multi-output Gaussian process (MOGP) with expressive covariance functions. Learning these market dependencies among financial series is crucial for the imputation and prediction of financial observations.

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Authors:
Taco de Wolff, Alejandro Cuevas, Felipe Tobar
Submitted On:
13 May 2020 - 5:24pm
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[1] Taco de Wolff, Alejandro Cuevas, Felipe Tobar, "Gaussian process imputation of multiple financial series", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5150. Accessed: Aug. 06, 2020.
@article{5150-20,
url = {http://sigport.org/5150},
author = {Taco de Wolff; Alejandro Cuevas; Felipe Tobar },
publisher = {IEEE SigPort},
title = {Gaussian process imputation of multiple financial series},
year = {2020} }
TY - EJOUR
T1 - Gaussian process imputation of multiple financial series
AU - Taco de Wolff; Alejandro Cuevas; Felipe Tobar
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5150
ER -
Taco de Wolff, Alejandro Cuevas, Felipe Tobar. (2020). Gaussian process imputation of multiple financial series. IEEE SigPort. http://sigport.org/5150
Taco de Wolff, Alejandro Cuevas, Felipe Tobar, 2020. Gaussian process imputation of multiple financial series. Available at: http://sigport.org/5150.
Taco de Wolff, Alejandro Cuevas, Felipe Tobar. (2020). "Gaussian process imputation of multiple financial series." Web.
1. Taco de Wolff, Alejandro Cuevas, Felipe Tobar. Gaussian process imputation of multiple financial series [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5150

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