Handwritten digit classification using higher order singular value decomposition B Savas, L Eldén Pattern recognition 40 (3), 993-1003, 2007 | 290 | 2007 |

A Newton–Grassmann Method for Computing the Best Multilinear Rank- Approximation of a Tensor L Eldén, B Savas SIAM Journal on Matrix Analysis and applications 31 (2), 248-271, 2009 | 189 | 2009 |

Quasi-Newton methods on Grassmannians and multilinear approximations of tensors B Savas, LH Lim SIAM Journal on Scientific Computing 32 (6), 3352-3393, 2010 | 177* | 2010 |

Supervised link prediction using multiple sources Z Lu, B Savas, W Tang, IS Dhillon 2010 IEEE international conference on data mining, 923-928, 2010 | 168 | 2010 |

Clustered low rank approximation of graphs in information science applications B Savas, IS Dhillon Proceedings of the 2011 SIAM International Conference on Data Mining, 164-175, 2011 | 78 | 2011 |

Krylov-type methods for tensor computations I B Savas, L Eldén Linear Algebra and its Applications 438 (2), 891-918, 2013 | 57* | 2013 |

Analyses and tests of handwritten digit recognition algorithms B Savas LiTH-MAT-EX-2003-01, Linkˆping University, Department of Mathematics, 2003 | 54* | 2003 |

Scalable affiliation recommendation using auxiliary networks V Vasuki, N Natarajan, Z Lu, B Savas, I Dhillon ACM Transactions on Intelligent Systems and Technology (TIST) 3 (1), 1-20, 2011 | 51 | 2011 |

Parallel clustered low-rank approximation of graphs and its application to link prediction X Sui, TH Lee, JJ Whang, B Savas, S Jain, K Pingali, I Dhillon Languages and Compilers for Parallel Computing: 25th International Workshop …, 2013 | 25 | 2013 |

Clustered embedding of massive social networks HH Song, B Savas, TW Cho, V Dave, Z Lu, IS Dhillon, Y Zhang, L Qiu ACM SIGMETRICS Performance Evaluation Review 40 (1), 331-342, 2012 | 22 | 2012 |

Perturbation theory and optimality conditions for the best multilinear rank approximation of a tensor L Elden, B Savas SIAM journal on matrix analysis and applications 32 (4), 1422-1450, 2011 | 15 | 2011 |

Algorithms in data mining using matrix and tensor methods B Savas Matematiska institutionen, 2008 | 13 | 2008 |

Rank reduction and volume minimization approach to state-space subspace system identification B Savas, D Lindgren Signal processing 86 (11), 3275-3285, 2006 | 12 | 2006 |

Clustered matrix approximation B Savas, IS Dhillon SIAM Journal on Matrix Analysis and Applications 37 (4), 1531-1555, 2016 | 9 | 2016 |

The maximum likelihood estimate in reduced‐rank regression L Eldén, B Savas Numerical linear algebra with applications 12 (8), 731-741, 2005 | 9 | 2005 |

Big Data D Zhang, MHJ Sidik Artificial Intelligence, and Financial Literacy: Exploring their Combined …, 2024 | 6 | 2024 |

Dimensionality reduction and volume minimization—generalization of the determinant minimization criterion for reduced rank regression problems B Savas Linear algebra and its applications 418 (1), 201-214, 2006 | 5 | 2006 |

Algorithm Package Manual: Best Low Rank Tensor Approximation B Savas Department of Mathematics, Linköping Univeristy, Linköping, Sweden, 2008 | 2 | 2008 |

Social Network Analysis: Fast and Memory-Efficient Low-Rank Approximation of Massive Graphs I Dhillon, B Savas, Y Zhang Householder Symposium XVIII on Numerical Linear Algebra, 55, 2011 | 1 | 2011 |

Toolbox for Grassmann Manifold Computations B Savas Department of Mathematics, Linköping Univeristy, Linköping, Sweden, 2008 | 1 | 2008 |