Alex Gittens
Alex Gittens
Assistant Professor of Computer Science, Rensselaer Polytechnic Institute
Verified email at - Homepage
Cited by
Cited by
Revisiting the nystrom method for improved large-scale machine learning
A Gittens, M Mahoney
International Conference on Machine Learning, 567-575, 2013
Revisiting the Nyström method for improved large-scale machine learning
A Gittens, MW Mahoney
The Journal of Machine Learning Research 17 (1), 3977-4041, 2016
Improved matrix algorithms via the subsampled randomized Hadamard transform
C Boutsidis, A Gittens
SIAM Journal on Matrix Analysis and Applications 34 (3), 1301-1340, 2013
Compact random feature maps
R Hamid, Y Xiao, A Gittens, D DeCoste
International Conference on Machine Learning, 19-27, 2014
The spectral norm error of the naive Nystrom extension
A Gittens
arXiv preprint arXiv:1110.5305, 2011
Matrix factorizations at scale: A comparison of scientific data analytics in Spark and C+ MPI using three case studies
A Gittens, A Devarakonda, E Racah, M Ringenburg, L Gerhardt, ...
2016 IEEE International Conference on Big Data (Big Data), 204-213, 2016
Skip-Gram− Zipf+ Uniform= Vector Additivity
A Gittens, D Achlioptas, MW Mahoney
Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017
Tail bounds for all eigenvalues of a sum of random matrices
A Gittens, JA Tropp
arXiv preprint arXiv:1104.4513, 2011
The masked sample covariance estimator: an analysis using matrix concentration inequalities
RY Chen, A Gittens, JA Tropp
Information and Inference: A Journal of the IMA 1 (1), 2-20, 2012
Sketched ridge regression: Optimization perspective, statistical perspective, and model averaging
S Wang, A Gittens, MW Mahoney
The Journal of Machine Learning Research 18 (1), 8039-8088, 2017
Spectral clustering via the power method-provably
C Boutsidis, P Kambadur, A Gittens
International conference on machine learning, 40-48, 2015
Scalable kernel K-means clustering with Nyström approximation: relative-error bounds
S Wang, A Gittens, MW Mahoney
The Journal of Machine Learning Research 20 (1), 431-479, 2019
Breaking locality accelerates block Gauss-Seidel
S Tu, S Venkataraman, AC Wilson, A Gittens, MI Jordan, B Recht
arXiv preprint arXiv:1701.03863, 2017
H5spark: bridging the I/O gap between spark and scientific data formats on Hpc systems
J Liu, E Racah, Q Koziol, RS Canon, A Gittens
Cray user group, 2016
Approximate spectral clustering via randomized sketching
A Gittens, P Kambadur, C Boutsidis
Ebay/IBM Research Technical Report, 2013
Error bounds for random matrix approximation schemes
A Gittens, JA Tropp
arXiv preprint arXiv:0911.4108, 2009
Synthesis, structure and characterization of two new antimony oxides–LaSb 3 O 9 and LaSb 5 O 12: Formation of LaSb 5 O 12 from the reaction of LaSb 3 O 9 with Sb 2 O 3
KM Ok, A Gittens, L Zhang, PS Halasyamani
Journal of Materials Chemistry 14 (1), 116-120, 2004
Texture‐based tissue characterization for high‐resolution CT scans of coronary arteries
M Papadakis, BG Bodmann, SK Alexander, D Vela, S Baid, AA Gittens, ...
Communications in numerical methods in engineering 25 (6), 597-613, 2009
Topics in randomized numerical linear algebra
AA Gittens
California Institute of Technology, 2013
Tensor machines for learning target-specific polynomial features
J Yang, A Gittens
arXiv preprint arXiv:1504.01697, 2015
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