Randomized sketches for kernel CCA. (July 2020)
- Record Type:
- Journal Article
- Title:
- Randomized sketches for kernel CCA. (July 2020)
- Main Title:
- Randomized sketches for kernel CCA
- Authors:
- Lian, Heng
Zhang, Fode
Lu, Wenqi - Abstract:
- Abstract: Kernel canonical correlation analysis (KCCA) is a popular tool as a nonlinear extension of canonical correlation analysis. Consistency and optimal convergence rate have been established in the literature. However, the time complexity of KCCA scales as O ( n 3 ) and is thus prohibitive when n is large. We propose an m -dimensional randomized sketches approach for KCCA with m < < n, based on the recent work on randomized sketches for kernel ridge regression (KRR). Technically we establish our theoretical results relying on an interesting connection between KCCA and KRR by utilizing a novel "duality tracking" device that alternates between the infinite-dimensional operator-theory-based view of KCCA and the finite-dimensional kernel-matrix-based view.
- Is Part Of:
- Neural networks. Volume 127(2020)
- Journal:
- Neural networks
- Issue:
- Volume 127(2020)
- Issue Display:
- Volume 127, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 127
- Issue:
- 2020
- Issue Sort Value:
- 2020-0127-2020-0000
- Page Start:
- 29
- Page End:
- 37
- Publication Date:
- 2020-07
- Subjects:
- Canonical correlation analysis -- Covariance/cross-covariance operator -- Kernel method -- Random projection
Neural computers -- Periodicals
Neural networks (Computer science) -- Periodicals
Neural networks (Neurobiology) -- Periodicals
Nervous System -- Periodicals
Ordinateurs neuronaux -- Périodiques
Réseaux neuronaux (Informatique) -- Périodiques
Réseaux neuronaux (Neurobiologie) -- Périodiques
Neural computers
Neural networks (Computer science)
Neural networks (Neurobiology)
Periodicals
006.32 - Journal URLs:
- http://www.sciencedirect.com/science/journal/08936080 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.neunet.2020.04.006 ↗
- Languages:
- English
- ISSNs:
- 0893-6080
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6081.280800
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British Library HMNTS - ELD Digital store - Ingest File:
- 13449.xml