Low Redundancy Estimation of Correlation Matrices for Time Series Using Triangular Bounds

Erik Scharwächter, Fabian Geier, Lukas Faber, Emmanuel Müller. Low Redundancy Estimation of Correlation Matrices for Time Series Using Triangular Bounds. In Dinh Q. Phung, Vincent S. Tseng, Geoffrey I. Webb, Bao Ho, Mohadeseh Ganji, Lida Rashidi, editors, Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part II. Volume 10938 of Lecture Notes in Computer Science, pages 458-470, Springer, 2018. [doi]

@inproceedings{ScharwachterGFM18,
  title = {Low Redundancy Estimation of Correlation Matrices for Time Series Using Triangular Bounds},
  author = {Erik Scharwächter and Fabian Geier and Lukas Faber and Emmanuel Müller},
  year = {2018},
  doi = {10.1007/978-3-319-93037-4_36},
  url = {https://doi.org/10.1007/978-3-319-93037-4_36},
  researchr = {https://researchr.org/publication/ScharwachterGFM18},
  cites = {0},
  citedby = {0},
  pages = {458-470},
  booktitle = {Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part II},
  editor = {Dinh Q. Phung and Vincent S. Tseng and Geoffrey I. Webb and Bao Ho and Mohadeseh Ganji and Lida Rashidi},
  volume = {10938},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-93037-4},
}