Submitted Preprints
- [S4] B. Bell, M. Geyer, D. Glickenstein, K. Hamm, C. Scheidegger, A. Fernandez, and J. Moore, Persistent Classification: Understanding Adversarial Attacks by Studying Decision Boundary Dynamics (25 pages, Minor Revisions Submitted)
- [S3] K. Hamm, C. Moosmüller, B. Schmitzer, M. Thorpe, Manifold learning in Wasserstein space (50 pages, Revisions submitted)
- [S2] K. Hamm, Z. Lu, W. Ouyang, and H. Zhang, Boosting Nystrom Method (Approximately 12 pages, Under Revision)
- [S1] K. Hamm and V. Khurana, Wasserstein approximation schemes based on Voronoi partitions (Approximately 14 pages, Submitted)
Peer-Reviewed Journal Articles
- [J21] A. Cloninger, K. Hamm, V. Khurana, and C. Moosmüller, Linearized Wasserstein Dimensionality Reduction with Approximation Guarantees Applied and Computational Harmonic Analysis, In Press. Approximatly 40 pages.
- [J20] K. Hamm and A. Korzeniowski, On Wasserstein Distances for Affine Transformations of Random Vectors Foundations of Data Science, 6(4) (2024), 468-491. Journal Version.
- [J19] K. Hamm, N. Henscheid, and S. Kang, Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning SIAM Journal on Mathematics of Data Science, 5(2) (2023), 475-501. Journal Version.
- [J18] K. Hamm, Generalized Pseudoskeleton Decompositions Linear Algebra and its Applications, Vol. 664 (2023) 236-252. Journal Version.
- [J17] H.Q. Cai, K. Hamm, L.-X. Huang, and Deanna Needell Mode-wise Tensor Decompositions: Multidimensional Generalizations of CUR Decompositions Journal of Machine Learning Research, Vol. 22 (2021), 1-36.
- [J16] H.Q. Cai, K. Hamm, L.-X. Huang, and Deanna Needell Robust CUR Decompositions: Theory and Imaging Applications, SIAM Journal on Imaging Sciences 14(4) (2021), 1472-1503. Journal Version
- [J15] K. Hamm, B. Hayes, and A. Petrosyan, An Operator Theoretic Approach to the Convergence of Rearranged Fourier Series Journal d’Analyse Mathématique, Vol. 143 (2021), 503-534. Journal Version, Video of ICERM Presentation
- [J14] K. Hamm and L.-X. Huang, Perturbations of CUR Decompositions SIAM Journal on Matrix Analysis and Applications, Vol. 42, No. 1 (2021), 351-375. Journal Version
- [J13] H.Q. Cai, K. Hamm, L.-X. Huang, Jiaqi Li, and Tao Wang Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank Estimation IEEE Signal Processing Letters, Vol. 28 (2021), 116-120. Journal Version
- [J12] R. Ahmed, G. Bodwin, F. Darabi Sahneh, K. Hamm, S. Kobourov, M. J. Latifi Jebelli, and R. Spence, Graph Spanners: A Tutorial Review Computer Science Review Vol 37 (2020), 100253. Journal Version
- [J11] K. Hamm and L.-X. Huang, Stability of Sampling for CUR Decompositions Foundations of Data Science Vol. 2, No. 2 (2020), 83-99. Journal Version
- [J10] K. Hamm and L.-X. Huang, Perspectives on CUR Decompositions Applied and Computational Harmonic Analysis Vol. 48, No. 3 (2020), 1088-1099. Journal Version
- [J9] A. Aldroubi, K. Hamm, A. B. Koku, and A. Sekmen, CUR Decompositions, Similarity Matrices, and Subspace Clustering, Frontiers in Applied Mathematics and Statistics — Mathematics of Computation and Data Science Section, Vol. 4, Article 65 (2019), 1-16. Journal Version (Open Access), Video
- [J8] K. Hamm, On the Gibbs–Wilbraham Phenomenon for Sampling and Interpolatory Series, Proceedings of the Edinburgh Mathematical Society, Vol. 62 (2019), 1163-1171. Journal Version
- [J7] K. Hamm and J. Ledford, Regular Families of Kernels for Nonlinear Approximation, Journal of Mathematical Analysis and Applications, Vol. 475, Issue 2 (2019), 1317-1340. Journal Version
- [J6] K. Hamm and J. Ledford, On the Structure and Interpolation Properties of Quasi Shift-Invariant Spaces, Journal of Functional Analysis, Vol. 274, Issue 7 (2018), 1959-1992. Journal Version
- [J5] K. Hamm and J. Ledford, Cardinal Interpolation With General Multiquadrics: Convergence Rates, Advances in Computational Mathematics, Vol. 44, Issue 4 (2018), 1205-1233. Journal Version
- [J4] J.-L. Bouchot and K. Hamm, Stability and Robustness of RBF Interpolation, Sampling Theory in Signal and Image Processing, Vol. 16 (2017), 37-53. Journal Version
- [J3] K. Hamm, Nonuniform Sampling and Recovery of Bandlimited Functions in Higher Dimensions, Journal of Mathematical Analysis and Applications, Vol. 450, Issue 2 (2017), 1459-1478. Journal Version
- [J2] K. Hamm and J. Ledford, Cardinal Interpolation With General Multiquadrics, Advances in Computational Mathematics, Vol. 42, Issue 5 (2016), 1149-1186. Journal Version
- [J1] K. Hamm, Approximation Rates for Interpolation of Sobolev Functions via Gaussians and Allied Functions, Journal of Approximation Theory, Vol. 189 (2015), 101-122. Journal Version
Dissertation
- [0] On the Interpolation of Smooth Functions via Radial Basis Functions, PhD Dissertation, Texas A&M University, 2015.
Refereed Conference Papers
- [C12] R. Ahmed, K. Hamm, S. Kobourov, M. J. Latifi Jebelli, F. D. Sahneh, and R. Spence, Multi-Priority Graph Sparsification, 34th International Workshop on Combinatorial Algorithms (IWOCA 2023). Conference Version
- [C11] K. Hamm, M. Meskini, and H.Q. Cai, Riemannian CUR decompositions for robust principal component analysis, Topological, Algebraic and Geometric Learning Workshops 2022. PMLR, 2022.
- [C10] R. Ahmed, Greg Bodwin, Keaton Hamm, Stephen Kobourov, and R. Spence, On Additive Spanners in Weighted Graphs with Local Error 47th International Workshop on Graph-Theoretic Concepts in Computer Science (WG 2021), Warsaw, Poland. Conference Version
- [C9] R. Ahmed, Greg Bodwin, Faryad Darabi Sahneh, Keaton Hamm, Stephen Kobourov, and R. Spence, Multi-level Weighted Additive Spanners 19th Symposium on Experimental Algorithms (SEA 2021). Conference Version
- [C8] R. Ahmed, F. Darabi Sahneh, K. Hamm, S. Kobourov, and R. Spence, Kruskal-based approximation algorithm for the multi-level Steiner tree problem, European Symposium on Algorithms (ESA) 2020. Conference Version
- [C7] R. Ahmed, K. Hamm, M. J. Latifi Jebelli, S. Kobourov, F. Sahneh, and R. Spence, Approximation Algorithms and an Integer Program for Multi-Level Graph Spanners, Proceedings of the Special Event on Analysis of Experimental Algorithms 2019, Kalamata, Greece. Conference Version
- [C6] K. Hamm and L.-X. Huang, On Column-Row Matrix Approximations, 13th International Conference on Sampling Theory and Applications (SampTA 2019), Bordeaux, France. Conference Version
- [C5] K. Hamm, B. Hayes, and A. Petrosyan, Rearranged Fourier Series and Generalizations to Non–Commutative Groups, 13th International Conference on Sampling Theory and Applications (SampTA 2019), Bordeaux, France. Conference Version
- [C4] A. Sekmen, A. Aldroubi, A. B. Koku, and K. Hamm, Principal Coordinate Clustering, 2017 IEEE International Conference on Big Data, Boston, MA, 2095-2102. Conference Version
- [C3] A. Sekmen, A. Aldroubi, K. Hamm, and A. B. Koku, Matrix Reconstruction: Skeleton Decomposition versus Singular Value Decomposition, Proceedings of the 2017 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS), Seattle, Washington. Conference Version
- [C2] K. Hamm and J. Ledford, On Bases of Cardinal Functions and Their Role in Approximate Sampling Methods, Proceedings of the 12th International Conference on Sampling Theory and Applications (SampTA 2017), Tallin, Estonia. Conference Version
- [C1] K. Hamm, Sampling and Recovery Using Multiquadrics, Proceedings of the 11th International Conference on Sampling Theory and Applications (SampTA 2015), Washington D.C. Conference Version
Other Works
- [A] K. Hamm and L.-X. Huang, CUR Decompositions, Approximations, and Perturbations, Approximately 40 pages. (Due to referee feedback, this article was split and resubmitted, and is mostly replaced by [11], [12], and [14] above; however, this version has a survey element that does not appear in the other versions and is a self-contained exposition.)
- [B] Mini-course slides from the CIMAT/TRIPODS Workshop in Guanajuato, Guanajuato, Mexico, 2019.
- [C] Mini-course slides from the Workshop in Harmonic Analysis, Sampling Theory, Machine Learning, and Data Science, Buenos Aires, Argentina, 2022.
Research Profiles
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