I am a Senior Research Scientist at IBM Research. Prior to my current role I was a Herman H. Goldstine Memorial Postdoctoral Fellow. I received my PhD (2018) and M.Sc (2016) in Computer Science and Engineering from the University of Minnesota, Twin Cities, U.S. My dissertation is titled "Domain decomposition algorithms for the solution of sparse symmetric generalized eigenvalue problems" and was supervised by Prof. Yousef Saad. Prior to that, I received M.Sc (2014) and M.Eng (2011) in Computer Engineering and Informatics from the University of Patras, Greece.
This is my personal homepage. If you are looking for my IBM webpage, click
here.
A list of my publications and related software can be found below.
Click here for a list of awards and honors.
Click here
for a list of patents.
[In memory of Theodoros Salonidis (1974-2023).]
Bibtex file: click
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[31.] Asynchronous Randomized Trace Estimation V. Kalantzis, S. Ubaru, C. W. Wu, G. Kollias, and L. Horesh In Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024) [Acceptance rate: 28%] |
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[30.] Topological Data Analysis on Noisy Quantum Computers I. Y. Akhalwaya, S. Ubaru, K. L. Clarkson, M. S. Squillante, V. Jejjala, Y. He, K. Naidoo, V. Kalantzis, and L. Horesh In Proceedings of the 12th International Conference on Learning Representations (ICLR 2024) Selected for oral presentation (1.2% of total submissions) [Acceptance rate: 31%] |
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[29.] Solving Sparse Linear Systems via Flexible GMRES with In-Memory Analog Preconditioning V. Kalantzis et al. In Proceedings of the 27th IEEE Conference on High Performance Extreme Computing (HPEC 2023) |
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[28.] A Parallel Algorithm for Computing Partial Spectral Factorizations of Matrix Pencils via Chebyshev Approximation T. Xu, A. P. Austin, V. Kalantzis, and Y. Saad SIAM Journal on Scientific Computing (2023), pp. S324-S351 DOI: 10.1137/22M1501155 Software: Github |
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[27.] Rayleigh-Ritz based updates of the Multilinear Singular Value Decomposition V. Kalantzis and P. Traganitis In Proceedings of the IEEE 57th Annual Asilomar Conference on Signals, Systems and Computers |
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[26.] Matrix Resolvent Eigenembeddings for Dynamic Graphs V. Kalantzis and P. Traganitis In Proceedings of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023) DOI: 10.1109/ICASSP49357.2023.10096476 |
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[25.] Quantum Graph Transformers G. Kollias, V. Kalantzis, T. Salonidis, and S. Ubaru In Proceedings of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023) DOI: 10.1109/ICASSP49357.2023.10096345 |
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[24.] Accelerating Matrix Trace Estimators by Aitken’s Δ-squared Process V. Kalantzis, G. Kollias, S. Ubaru, and T. Salonidis In Proceedings of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023) DOI: 10.1109/ICASSP49357.2023.10095081 |
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[23.] On Quantum Algorithms for Random Walks in the Nonnegative Quarter Plane V. Kalantzis, M. S. Squillante, S. Ubaru, and L. Horesh ACM SIGMETRICS Performance Evaluation Review 50 (2), pp. 42-44 DOI: 10.1145/3561074.3561089 |
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[22.] parGeMSLR: A Parallel Multilevel Schur Complement Low-Rank Preconditioning and
Solution Package for General Sparse Matrices T. Xu, V. Kalantzis, R. Li, Y. Xi, G. Dillon, and Y. Saad Parallel Computing (2022), Vol. 113 DOI: 10.1016/j.parco.2022.102956 Software: Github |
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[21.] Enhanced Algebraic Substructuring for Symmetric Generalized Eigenvalue Problems V. Kalantzis and L. Horesh Numerical Linear Algebra with Applications (2022), Vol. 30, No. 2 DOI: 10.1002/nla.2473 |
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[20.] Directed Graph Auto-Encoders G. Kollias, V. Kalantzis, T. Ide, A. Lozano, and N. Abe In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022) [Acceptance rate: 15%] DOI: 10.1609/aaai.v36i7.20682 Software: Github |
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[19.] Solving Sparse Linear Systems with Approximate Inverse Preconditioners on Analog Devices V. Kalantzis et al. In Proceedings of the 25th IEEE Conference on High Performance Extreme Computing (HPEC 2021) DOI: 10.1109/HPEC49654.2021.9622816 |
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[18.] Fast Randomized non-Hermitian Eigensolvers Based on Rational Filtering and Matrix Partitioning V. Kalantzis, Y. Xi, and L. Horesh SIAM Journal on Scientific Computing (2021), Vol. 43, No. 5, pp. S791-S815 DOI: 10.1137/19M1280004 |
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[17.] Projection Techniques to Update the Truncated SVD of Evolving Matrices with Applications V. Kalantzis, G. Kollias, S. Ubaru, A. N. Nikolakopoulos, L. Horesh, and K. L. Clarkson In Proceedings of the 38th International Conference on Machine Learning (ICML 2021) [Acceptance rate: 21%] Proceedings of Machine Learning Research |
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[16.] Sparse Graph-Based Sketching for Numerical Linear Algebra D. Hu, S. Ubaru, A. Gittens, L. Horesh, K. L. Clarkson, and V. Kalantzis In Proceedings of the 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021) DOI: 10.1109/ICASSP39728.2021.9414030 |
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[15.] A Domain Decomposition Rayleigh-Ritz Algorithm for Symmetric Generalized Eigenvalue Problems V. Kalantzis SIAM Journal on Scientific Computing (2020), Vol. 42, No. 6, pp. C410-C435 DOI: 10.1137/19M1280004 |
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[14.] A Spectral Newton-Schur Algorithm for the Solution of Symmetric Generalized
Eigenvalue Problems V. Kalantzis Electronic Transactions on Numerical Analysis (2020), Vol. 52, pp. 132-153 DOI: 10.1553/etna_vol52s132 |
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[13.] TeraPCA: a Fast and Scalable Method to Study Genetic Variation in Tera-scale Genotypes A. Bose, V. Kalantzis, E. M. Kontopoulou, M. Elkadi, P. Paschou, and P. Drineas Bioinformatics (2019), Volume 35, Issue 19, pp. 3679-3683 DOI: 10.1093/bioinformatics/btz157 Software: C++ |
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[12.] Stable Computation of Generalized Matrix Functions via Polynomial Interpolation J. L. Aurentz, A. P. Austin, M. Benzi, and V. Kalantzis SIAM Journal on Matrix Analysis and Applications (2019), Vol. 40, No. 1, pp. 210-234 DOI: 10.1137/18M1191786 |
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[-.] Domain Decomposition Algorithms for the Solution of Sparse Symmetric Generalized Eigenvalue Problems V. Kalantzis Ph. D. Thesis (2018), University of Minnesota, Twin Cities Public access: http://hdl.handle.net/11299/201170 |
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[11.] Beyond Automated Multilevel Substructuring: Domain Decomposition with Rational Filtering V. Kalantzis, Y. Xi, and Y. Saad SIAM Journal on Scientific Computing (2018), Vol. 40, No. 4, pp. C477-C502 DOI: 10.1137/17M1154527 |
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[10.] A Hierarchical Low-Rank Schur Complement Preconditioner for Indefinite Linear Systems G. Dillon, V. Kalantzis, Y. Xi, and Y. Saad SIAM Journal on Scientific Computing (2018), Vol. 40, No. 4, pp. A2234-A2252 DOI: 10.1137/17M1143320 |
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[9.] Domain Decomposition Approaches for Accelerating Contour Integration Eigenvalue Solvers for Symmetric Eigenvalue Problems V. Kalantzis, J. Kestyn, E. Polizzi, and Y. Saad Numerical Linear Algebra with Applications (2018), Vol. 25, No. 5 DOI: 10.1002/nla.2154 |
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[8.] A Scalable Iterative Dense Linear System Solver for Multiple Right-Hand Sides in Data Analytics V. Kalantzis, C. Malossi, C. Bekas, A. Curioni, E. Gallopoulos, and Y. Saad Parallel Computing (2018), Vol. 74, pp. 136-153 DOI: 10.1016/j.parco.2017.12.005 Software: Fortran |
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[7.] EIGENREC: Generalizing PureSVD for Effective and Efficient Top-N Recommendations A. N. Nikolakopoulos, V. Kalantzis, E. Gallopoulos, and J. D. Garofalakis Knowledge and Information Systems (2018), Vol. 58, No. 1, pp. 59-81 DOI: 10.1007/s10115-018-1197-7 |
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[6.] Factored Proximity Models for Top-N Recommendations A. N. Nikolakopoulos, V. Kalantzis, E. Gallopoulos, and J. D. Garofalakis In Proceedings of the 8th IEEE International Conference on Big Knowledge (ICBK 2017) [Acceptance rate: 27%] DOI: 10.1109/ICBK.2017.14 Software: Fortran |
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[5.] Cucheb: A GPU Implementation of the Filtered Lanczos Procedure J. L. Aurentz, V. Kalantzis, and Y. Saad Computer Physics Communications (2017), Vol. 220, pp. 332-340 DOI: 10.1016/j.cpc.2017.06.016 Software: C++/CUDA |
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[4.] PFEAST: A High Performance Sparse Eigenvalue Solver Using Distributed-Memory Linear Solvers J. Kestyn, V. Kalantzis, E. Polizzi, and Y. Saad In Proceedings of the 2016 ACM/IEEE Supercomputing Conference (SC 2016) [Acceptance rate: 18%] DOI: 10.1109/SC.2016.15 |
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[3.] Spectral Schur Complement Techniques for Symmetric Eigenvalue Problems V. Kalantzis, R. Li, and Y. Saad Electronic Transactions on Numerical Analysis (2016), Vol. 45, pp. 305-329 |
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[2.] Estimating the Trace of the Matrix Inverse by Interpolating from the Diagonal of an Approximate Inverse L. Wu, J. Laeuchli, V. Kalantzis, A. Stathopoulos, and E. Gallopoulos Journal of Computational Physics (2016), Vol. 326, pp. 828-844 DOI: 10.1016/j.jcp.2016.09.001 |
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[1.] Accelerating Data Uncertainty Quantification by Solving Linear Systems with Multiple Right-Hand Sides V. Kalantzis, C. Bekas, A. Curioni, and E. Gallopoulos Numerical Algorithms (2013), Vol. 62, No. 4, pp. 637-653 DOI: 10.1007/s11075-012-9687-2 |
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Some of the preprint papers and/or personal copies of accepted papers provided above might differ from the actual published versions. Please refer to the corresponding journals/conference proceedings for the final versions. Any opinions, statements, or conclusions expressed in the above reports do not necessarily reflect the views of the acknowledged funding sponsors or International Business Machines Corporation, Inc.
The layout of this webpage was copied from Anthony P. Austin's personal webpage.