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MODELLING LARGE SCALE DATASETS USING PARTITIONING-BASED PCA

Abstract: 

In this study, we propose an efficient approach for modelling and compressing large-scale datasets. The main idea is to subdivide each sample into smaller partitions where each partition constitutes a particular subset of attributes and then apply PCA to each partition separately. This simple approach enjoys several key advantages over the traditional holistic scheme in terms of reduced computational cost and enhanced reconstruction quality. We study two variants of this approach, namely, cell-based PCA for image datasets where samples are spatially divided into smaller blocks and the more general band-based PCA where attributes are partitioned based on their values distribution.

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Paper Details

Authors:
Salaheddin Alakkari, John Dingliana
Submitted On:
20 September 2019 - 12:08am
Short Link:
Type:
Poster
Event:
Paper Code:
3447
Document Year:
2019
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Document Files

ICIP-poster_v3.pdf

(5)

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[1] Salaheddin Alakkari, John Dingliana, "MODELLING LARGE SCALE DATASETS USING PARTITIONING-BASED PCA", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4758. Accessed: Oct. 18, 2019.
@article{4758-19,
url = {http://sigport.org/4758},
author = {Salaheddin Alakkari; John Dingliana },
publisher = {IEEE SigPort},
title = {MODELLING LARGE SCALE DATASETS USING PARTITIONING-BASED PCA},
year = {2019} }
TY - EJOUR
T1 - MODELLING LARGE SCALE DATASETS USING PARTITIONING-BASED PCA
AU - Salaheddin Alakkari; John Dingliana
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4758
ER -
Salaheddin Alakkari, John Dingliana. (2019). MODELLING LARGE SCALE DATASETS USING PARTITIONING-BASED PCA. IEEE SigPort. http://sigport.org/4758
Salaheddin Alakkari, John Dingliana, 2019. MODELLING LARGE SCALE DATASETS USING PARTITIONING-BASED PCA. Available at: http://sigport.org/4758.
Salaheddin Alakkari, John Dingliana. (2019). "MODELLING LARGE SCALE DATASETS USING PARTITIONING-BASED PCA." Web.
1. Salaheddin Alakkari, John Dingliana. MODELLING LARGE SCALE DATASETS USING PARTITIONING-BASED PCA [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4758