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Tensor decompositions and machine learning

Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition

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Authors:
Yongjie Zhu, Xueqiao Li, Tapani Ristaniemi, Fengyu Cong
Submitted On:
8 May 2019 - 2:54am
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Brain_Networks_Tensor_Decomposition

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[1] Yongjie Zhu, Xueqiao Li, Tapani Ristaniemi, Fengyu Cong, "Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4029. Accessed: Oct. 24, 2020.
@article{4029-19,
url = {http://sigport.org/4029},
author = {Yongjie Zhu; Xueqiao Li; Tapani Ristaniemi; Fengyu Cong },
publisher = {IEEE SigPort},
title = {Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition},
year = {2019} }
TY - EJOUR
T1 - Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition
AU - Yongjie Zhu; Xueqiao Li; Tapani Ristaniemi; Fengyu Cong
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4029
ER -
Yongjie Zhu, Xueqiao Li, Tapani Ristaniemi, Fengyu Cong. (2019). Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition. IEEE SigPort. http://sigport.org/4029
Yongjie Zhu, Xueqiao Li, Tapani Ristaniemi, Fengyu Cong, 2019. Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition. Available at: http://sigport.org/4029.
Yongjie Zhu, Xueqiao Li, Tapani Ristaniemi, Fengyu Cong. (2019). "Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition." Web.
1. Yongjie Zhu, Xueqiao Li, Tapani Ristaniemi, Fengyu Cong. Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4029

SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING


In this paper, we address the fundamental problem of Sparse
Bayesian Learning (SBL), where the received signal is a high-order
tensor. We furthermore consider the problem of dictionary learning
(DL), where the tensor observations are assumed to be generated
from a Kronecker structured (KS) dictionary matrix multiplied by
the sparse coefficients. Exploiting the tensorial structure results in
a reduction in the number of degrees of freedom in the learning
problem, since the dimensions of each of the factor matrices are significantly

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Submitted On:
7 May 2019 - 12:58pm
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[1] , "SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3923. Accessed: Oct. 24, 2020.
@article{3923-19,
url = {http://sigport.org/3923},
author = { },
publisher = {IEEE SigPort},
title = {SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING},
year = {2019} }
TY - EJOUR
T1 - SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3923
ER -
. (2019). SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING. IEEE SigPort. http://sigport.org/3923
, 2019. SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING. Available at: http://sigport.org/3923.
. (2019). "SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING." Web.
1. . SPACE ALTERNATING VARIATIONAL ESTIMATION AND KRONECKER STRUCTURED DICTIONARY LEARNING [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3923

Tensor Ensemble Learning


In big data applications, classical ensemble learning is typically infeasible on the raw input data and dimensionality reduction techniques are necessary. To this end, novel framework that generalises classic flat-view ensemble learning to multidimensional tensor- valued data is introduced. This is achieved by virtue of tensor decompositions, whereby the proposed method, referred to as tensor ensemble learning (TEL), decomposes every input data sample into multiple factors which allows for a flexibility in the choice of multiple learning algorithms in order to improve test performance.

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Authors:
Ahmad Moniri
Submitted On:
23 November 2018 - 1:09pm
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IK_AM_DPM_GlobalSIP_2018_presentation.pdf

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[1] Ahmad Moniri, "Tensor Ensemble Learning", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3751. Accessed: Oct. 24, 2020.
@article{3751-18,
url = {http://sigport.org/3751},
author = {Ahmad Moniri },
publisher = {IEEE SigPort},
title = {Tensor Ensemble Learning},
year = {2018} }
TY - EJOUR
T1 - Tensor Ensemble Learning
AU - Ahmad Moniri
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3751
ER -
Ahmad Moniri. (2018). Tensor Ensemble Learning. IEEE SigPort. http://sigport.org/3751
Ahmad Moniri, 2018. Tensor Ensemble Learning. Available at: http://sigport.org/3751.
Ahmad Moniri. (2018). "Tensor Ensemble Learning." Web.
1. Ahmad Moniri. Tensor Ensemble Learning [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3751