final_report.bbl

\begin{thebibliography}{1}

\bibitem{net}
Felipe Cucker and Steve Smale.
\newblock On the mathematical foundations of learning.
\newblock {\em Bulletin of the American Mathematical Society}, 39:1--49, 2002.

\bibitem{algebra}
L.~(Ed.) Hogben.
\newblock {\em Handbook of Linear Algebra (2nd ed.)}.
\newblock Chapman and Hall/CRC., 2013.

\bibitem{svd_rank}
Hopcroft and Kannan.
\newblock Lecture notes (forthcoming book).
\newblock [EB/OL], 2012.
\newblock
  \url{https://www.cs.princeton.edu/courses/archive/spring12/cos598C/svdchapter.pdf}.

\bibitem{nmsemble}
Sanjiv Kumar, Mehryar Mohri, and Ameet Talwalkar.
\newblock Ensemble nystrom method.
\newblock In {\em Advances in Neural Information Processing Systems 22 -
  Proceedings of the 2009 Conference}, Advances in Neural Information
  Processing Systems 22 - Proceedings of the 2009 Conference, pages 1060--1068,
  2009.
\newblock 23rd Annual Conference on Neural Information Processing Systems, NIPS
  2009 ; Conference date: 07-12-2009 Through 10-12-2009.

\bibitem{kernel}
Jianbo Shi and J.~Malik.
\newblock Normalized cuts and image segmentation.
\newblock {\em IEEE Transactions on Pattern Analysis and Machine Intelligence},
  22(8):888--905, 2000.

\bibitem{meka}
Si~Si, Cho-Jui Hsieh, and Inderjit~S. Dhillon.
\newblock Memory efficient kernel approximation.
\newblock In {\em International Conference on Machine Learning (ICML)}, jun
  2014.

\bibitem{nm}
Christopher K.~I. Williams and Matthias~W. Seeger.
\newblock Using the nystr{\"o}m method to speed up kernel machines.
\newblock In {\em NIPS}, 2000.

\end{thebibliography}