Matrix methods in data mining and pattern recognition

@inproceedings{Elden2007MatrixMI,
  title={Matrix methods in data mining and pattern recognition},
  author={Lars Elden},
  booktitle={Fundamentals of algorithms},
  year={2007}
}
Preface Part I. Linear Algebra Concepts and Matrix Decompositions: 1. Vectors and matrices in data mining and pattern recognition 2. Vectors and matrices 3. Linear systems and least squares 4. Orthogonality 5. QR decomposition 6. Singular value decomposition 7. Reduced rank least squares models 8. Tensor decomposition 9. Clustering and non-negative matrix factorization Part II. Data Mining Applications: 10. Classification of handwritten digits 11. Text mining 12. Page ranking for a Web search… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 175 CITATIONS

Feature Fusion for Prediction of Theaflavin and Thearubigin in Tea Using Electronic Tongue

  • IEEE Transactions on Instrumentation and Measurement
  • 2017
VIEW 12 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

Multiple Queries of Information Retrieval Using Krylov Subspace Method

  • 2017 IEEE International Conference on Data Mining Workshops (ICDMW)
  • 2017
VIEW 5 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Citation Prediction Using Diverse Features

  • 2015 IEEE International Conference on Data Mining Workshop (ICDMW)
  • 2015
VIEW 8 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

The Singular Value Decomposition

VIEW 4 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

Farsi/Arabic handwritten digit recognition based on ensemble of SVD classifiers and reliable multi-phase PSO combination rule

  • International Journal on Document Analysis and Recognition (IJDAR)
  • 2012
VIEW 4 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

2006
2019

CITATION STATISTICS

  • 26 Highly Influenced Citations

  • Averaged 15 Citations per year from 2017 through 2019