Before joining Rensselaer as an Assistant Professor of Computer Science in 2017, Dr. Gittens was a research scientist at eBay Research Labs and a postdoctoral scholar at the International Institute of Computer Science and the Department of Statistics, UC Berkeley. His interests lie in applying randomness to computational linear algebra, machine learning, and statistics, and are motivated by the goal of efficiently extracting information from massive data sets while maintaining guarantees on rigor and accuracy.
B.S., Mathematics, University of Houston, 2006. B.S., Electrical Engineering, University of Houston, 2006. PhD., Applied and Computational Mathematics, California Institute of Technology, 2013.
- Alex Gittens and Michael W. Mahoney. "Revisiting the Nyström method for improved large-scale machine learning". The Journal of Machine Learning Research, Volume 17, 2016, 2016.
- Christos Boutsidis and Alex Gittens. "Improved matrix algorithms via the subsampled randomized Hadamard transform". SIAM Journal on Matrix Analysis and Applications, Volume 34, Number 3, 2013.
- Raffay Hamid and Ying Xiao and Alex Gittens and Dennis DeCoste. "Compact Random Feature Maps". ICML, 2014.
- Richard Y. Chen and Alex Gittens and Joel A. Tropp. "The masked sample covariance estimator: an analysis using matrix concentration inequalities". Information and Inference, Volume 1, Issue 1, 2012.
- Christos Boutsidis and Prabhanjan Kambadur and Alex Gittens. "Spectral Clustering via the Power Method-- Provably". ICML, 2015.
- Da Kuang and Alex Gittens and Raffay Hamid. "Hardware Compliant Approximate Image Codes". CVPR, 2015.
- Alex Gittens and Dimitris Achlioptas and Michael W. Mahoney. "Skip-Gram – Zipf + Uniform = Vector Additivity". ACL, 2017