Mirjeta Pasha
My research interests include Numerical Linear Algebra, Inverse Problems, UQ, Neural Networks, Data Science, and Tensor Computations.
Published and Accepted:
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Alessandro Buccini, Mirjeta Pasha, and Lothar Reichel. ``Linearized Krylov subspace Bregman iteration with nonnegativity constraint." Numer Algor (2020). https://doi.org/10.1007/s11075-020-01004-6
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Alessandro Buccini, Mirjeta Pasha, and Lothar Reichel. ``Generalized singular value decomposition with iterated Tikhonov regularization." Journal of Computational and Applied Mathematics 373 (2020):112276. https://doi.org/10.1016/j.cam.2019.05.024
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Alessandro Buccini, Mirjeta Pasha, and Lothar Reichel. ``Modulus-based iterative methods for constrained $\ell_p-\ell_q$ minimization." Inverse Problmes 36 (8) (2020). https://doi.org/10.1088/1361-6420/ab9f86
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Mirjeta Pasha, ``Krylov subspace type methods for the computation of non-negative or sparse solutions of ill-posed problems", OhioLink, (2020). http://rave.ohiolink.edu/etdc/view?acc_num=kent1586459362313778
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Mirjeta Pasha, Shyla Kupis, Sanwar Ahmad, and Taufiquar Khan. ``A Krylov subspace type method for Electrical Impedance Tomography", (2021).
Submitted:
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Yunan Yang, Levon Nurbekyan, Elisa Negrini, Robert Martin, and Mirjeta Pasha, ``Optimal Transport for Parameter Identication of Steady-State Chaotic Dynamics", (2021). https://arxiv.org/abs/2104.15138
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Malena Espanol and Mirjeta Pasha, ``An $\ell_p$ Variable Projection Method for Large-Scale Separable Nonlinear Inverse Problems", (2021), https://arxiv.org/abs/2105.14155
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Mirjeta Pasha, Arvind Saibaba, Silvia Gazzola, Malena Espanol, and Eric de Sturler, ``Efficient edge-preserving methods for dynamic inverse problems", (2021). https://arxiv.org/abs/2107.05727
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Julianne Chung, Matthias Chung, Silvia Gazzola, and Mirjeta Pasha, ``Efficient learning methods for large-scale optimal inversion design", (2021). https://arxiv.org/abs/2110.02720
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Hussam Al Daas, Grey Ballard, Paul Cazeaux, Agnieszka Miedlar, Mirjeta Pasha, Timothy Reid, and Arvind Saibaba, ``Randomized Algorithms for Tensor Train Decompositions". https://arxiv.org/abs/2110.04393
In preparation:
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Malena Espanol, Mirjeta Pasha, Rosalind Sadleir, ``EIT with limited data".
Software:
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Randomized Algorithms for Rounding in the Tensor Train Format, Al Daas, H. and Ballard, G. and Cazeaux, P. and Hallman, E. and Pasha, M. and Miedlar, A. and Reid, T.W. and Saibaba, A.K.
Courses
2022 Spring
Course Number | Course Title |
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APM 598 | Special Topics |
2021 Fall
Course Number | Course Title |
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MAT 342 | Linear Algebra |
MAT 275 | Modern Differential Equations |
2021 Spring
Course Number | Course Title |
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MAT 275 | Modern Differential Equations |
MAT 275 | Modern Differential Equations |
2020 Fall
Course Number | Course Title |
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MAT 275 | Modern Differential Equations |