Publications & Preprints

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Author [ Title(Desc)] Type Year
G
Vavasis, S. A. . (1989). Gaussian elimination with pivoting is P-complete. SIAM Journal on Discrete Mathematics, 2, 412–423.
Miller, G. L. , Teng, S. - H. , Thurston, W. , & Vavasis, S. . (1998). Geometric Separators for Finite-Element Meshes. SIAM J. Sci. Comput., 19, 364-386.
I
Vavasis, S. A. , & Ye, Y. . (1996). Identifying an Optimal Basis in Linear Programming. Annals of Operations Research, 62, 565–572.
Karimi, S. , & Vavasis, S. . (2017). IMRO: A Proximal Quasi-Newton Method for Solving $\ell_1$-Regularized Least Squares Problems. SIAM J. Optimiz, 27, 583-615.
Howle, V. E. , & Vavasis, S. A. . (2005). An iterative method for solving complex-symmetric systems arising in electrical power modeling. SIAM J. Matrix Analysis App., 26, 1150-1178.
L
Vavasis, S. A. . (1992). Local minima for indefinite quadratic knapsack problems. matpro, 54, 127–153.
Sastry, S. , Shontz, S. , & Vavasis, S. . (2012). A log-barrier method for mesh quality improvement. In Proceedings of 20th International Meshing Roundtable (pp. 329-346). Springer.
Doan, X. Vinh, & Vavasis, S. A. . (2022). Low-rank matrix recovery with Ky Fan 2-k-norm. Journal of Global Optimization, 82, 727-751. Retrieved from https://link.springer.com/article/10.1007/s10898-021-01031-0
Doan, X. V. , & Vavasis, S. . (2019). Low-rank matrix recovery with Ky Fan 2-k-norm. In Optimization of Complex Systems: Theory, Models and Applications (pp. 310-319).
M
Iverson, V. , & Vavasis, S. . (10040). Mean and Variance Estimation Complexity in Arbitrary Distributions via Wasserstein Minimization. Retrieved from https://arxiv.org/abs/2501.10172
Ang, A. , De Sterck, H. , & Vavasis, S. . (Accepted). MGProx: A nonsmooth multigrid proximal gradient method with adaptive restriction for strongly convex optimization. SIAM J. Optimization. Retrieved from https://arxiv.org/abs/2302.04077
Bond, D. M. , & Vavasis, S. A. . (1992). Multigrid for mixed boundary integral equations. In Proc. 1992 Copper Mountain Conference on Iterative Methods.
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Stern, J. M. , & Vavasis, S. A. . (1993). Nested dissection for sparse nullspace bases. simax, 14, 766–775.
Vavasis, S. A. . (2008). A new secant method for unconstrained optimization.
Karimi, S. , & Vavasis, S. A. . (Accepted). Nonlinear conjugate gradient for smooth convex functions. Mathematical Programming - Computation. Retrieved from https://arxiv.org/pdf/2111.11613.pdf
Vavasis, S. A. . (1991). Nonlinear Optimization: Complexity Issues. Oxford University Press.
Biggs, M. , Ghodsi, A. , & Vavasis, S. A. . (2008). Nonnegative matrix factorization via rank-one downdating. In Proceedings of the 2008 International Conference on Machine Learning.
Bobrovnikova, E. , & Vavasis, S. . (2000). A Norm Bound for Projections with Complex Weights. Linear Algebra and its Applications, 307, 69-75.
Vavasis, S. . (1999). A note on efficient computation of the gradient in semidefinite programming.
Vavasis, S. A. . (1990). A note on wavelet bases for two-dimensional surfaces. Department of Computer Science, Cornell University.

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