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Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis paper by Independent / Community
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Paper

Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis

by Independent / Community 002cd03320631c0f96ccc7b727d972c08ced7e3a
Free2AITools Nexus Index
69.8
S: Semantic 50

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A: Authority 86
P: Popularity 62
R: Recency 100
Q: Quality 65
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This paper considers the problem of canonical-correlation analysis (CCA) (Hotelling, 1936) and, more broadly, the generalized eigenvector problem for a pair of symmetric matrices. These are two fundamental problems in data analysis and scientific computing with numerous applications in machine learning and statistics (Shi and Malik, 2000; Hardoon et al., 2004; Witten et al., 2009). We provide simple iterative algorithms, with improved runtimes, for solving these problems that are globally li...

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Semantic Scholar 82 Citations
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Registry ID 002cd03320631c0f96ccc7b727d972c08ced7e3a
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BibTeX 
@misc{002cd03320631c0f96ccc7b727d972c08ced7e3a,
  author = {Unknown},
  title = {Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/002cd03320631c0f96ccc7b727d972c08ced7e3a}},
  note = {Accessed via Free2AITools.}
}
APA Style
Unknown. (2026). Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis [Paper]. Free2AITools. https://api.semanticscholar.org/002cd03320631c0f96ccc7b727d972c08ced7e3a

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Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 86
Popularity (P) 62
Recency (R) 100
Quality (Q) 65

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FNI V2.0 for Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis: Authority (A:86), Popularity (P:62), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

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πŸ“ Executive Summary

"This paper considers the problem of canonical-correlation analysis (CCA) (Hotelling, 1936) and, more broadly, the generalized eigenvector problem for a pair of symmetric matrices. These are two fundamental problems in data analysis and scientific computing with numerous applications in machine learning and statistics (Shi and Malik, 2000; Hardoon et al., 2004; Witten et al., 2009). We provide simple iterative algorithms, with improved runtimes, for solving these problems that are globally li..."

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@article{Unknown2026Efficient,
  title={Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

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πŸ“ˆ82CitationsSemantic Scholar
πŸ›οΈ86AuthorityFNI pillar
⏱️100RecencyFNI pillar
βœ…65QualityFNI pillar
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🏷️ Research Topics

vector databases
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author
Unknown
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ArXiv
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paper, research, academic

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