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Anna Little
Anna Little
Computational Mathematics, Science, and Engineering, Michigan State University
Verified email at msu.edu - Homepage
Title
Cited by
Cited by
Year
Multiscale geometric methods for data sets I: Multiscale SVD, noise and curvature
AV Little, M Maggioni, L Rosasco
Applied and Computational Harmonic Analysis 43 (3), 504-567, 2017
942017
Multiscale geometric methods for data sets I: Multiscale SVD, noise and curvature
AV Little, M Maggioni, L Rosasco
Applied and Computational Harmonic Analysis 43 (3), 504-567, 2017
942017
Multiscale estimation of intrinsic dimensionality of data sets
AV Little, YM Jung, M Maggioni
2009 AAAI Fall Symposium Series, 2009
722009
Estimation of intrinsic dimensionality of samples from noisy low-dimensional manifolds in high dimensions with multiscale SVD
AV Little, J Lee, YM Jung, M Maggioni
2009 IEEE/SP 15th Workshop on Statistical Signal Processing, 85-88, 2009
712009
Path-based spectral clustering: Guarantees, robustness to outliers, and fast algorithms
A Little, M Maggioni, JM Murphy
Journal of machine learning research 21 (6), 1-66, 2020
332020
Some recent advances in multiscale geometric analysis of point clouds
G Chen, AV Little, M Maggioni, L Rosasco
Wavelets and Multiscale Analysis: Theory and Applications, 199-225, 2011
252011
Multi-resolution geometric analysis for data in high dimensions
G Chen, AV Little, M Maggioni
Excursions in Harmonic Analysis, Volume 1: The February Fourier Talks at the …, 2013
222013
Multiscale geometric methods for estimating intrinsic dimension
AV Little, M Maggioni, L Rosasco
Proc. SampTA 4 (2), 2011
212011
Path-based spectral clustering: Guarantees, robustness to outliers, and fast algorithms
A Little, M Maggioni, JM Murphy
arXiv preprint arXiv:1712.06206, 2017
182017
Estimating the intrinsic dimension of high-dimensional data sets: a multiscale, geometric approach
AV Little
Duke University, 2011
152011
A multiscale spectral method for learning number of clusters
A Little, A Byrd
2015 IEEE 14th International Conference on Machine Learning and Applications …, 2015
132015
Balancing geometry and density: Path distances on high-dimensional data
A Little, D McKenzie, JM Murphy
SIAM Journal on Mathematics of Data Science 4 (1), 72-99, 2022
112022
Spectral clustering technique for classifying network attacks
A Little, X Mountrouidou, D Moseley
2016 IEEE 2nd International Conference on Big Data Security on Cloud …, 2016
112016
An analysis of classical multidimensional scaling with applications to clustering
A Little, Y Xie, Q Sun
Information and Inference: A Journal of the IMA 12 (1), 72-112, 2023
102023
Taxonomy of benchmarks in graph representation learning
R Liu, S Cantürk, F Wenkel, S McGuire, X Wang, A Little, L O’Bray, ...
Learning on Graphs Conference, 6: 1-6: 25, 2022
102022
An analysis of classical multidimensional scaling
A Little, Y Xie, Q Sun
arXiv preprint arXiv:1812.11954, 2018
102018
Multiscale geometric methods for data sets I: Estimation of intrinsic dimension
AV Little, M Maggioni, L Rosasco
preparation, 2010
92010
Wavelet invariants for statistically robust multi-reference alignment
M Hirn, A Little
Information and Inference: A Journal of the IMA 10 (4), 1287-1351, 2021
82021
Positive Solutions to a Diffusive Logistic Equation with Constant Yield Harvesting
T Ladner, A Little, K Marks, A Russell
Rose-Hulman Undergraduate Mathematics Journal 6 (1), 3, 2005
32005
On generalizations of the nonwindowed scattering transform
A Chua, M Hirn, A Little
Applied and Computational Harmonic Analysis 68, 101597, 2024
22024
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