update README

README.md

@@ -1,5 +1,5 @@
 # FrequentDirections
-Matlab code for deterministic matrix sketching using Frequent Directions (FD) variants. Implements the original and fast FD algorithms (Liberty, 2013) as well as a parameterization that varies smoothly between iterative SVD and FD (Desai et al, 2016).
+Matlab code for matrix sketching using Frequent Directions (FD) variants. Implements the original and fast FD algorithms (Liberty, 2013), a parameterization that varies smoothly between iterative SVD and FD (Desai et al, 2016), as well as a randomized variant suited for sparse inputs (Teng & Chu, 2017).
 
 ## Installation
 Add the single file [`FrequentDirections.m`](https://github.com/brian-lau/FrequentDirections/blob/master/FrequentDirections.m) to your Matlab path. Adding the directory `Examples` to the path is useful for running the examples. Unit tests can be run from the `Testing` directory.
@@ -37,6 +37,7 @@ The script [`exampleDesai.m`](https://github.com/brian-lau/FrequentDirections/bl
 * Desai, A., Ghashami, M., & Phillips, J. M. (2016). [Improved practical matrix sketching with guarantees](http://ieeexplore.ieee.org/abstract/document/7429755/). IEEE Transactions on Knowledge and Data Engineering, 28(7), 1678-1690.
 * Ghashami, M., Liberty, E., Phillips, J. M., & Woodruff, D. P. (2016). [Frequent directions: Simple and deterministic matrix sketching](http://epubs.siam.org/doi/abs/10.1137/15M1009718?journalCode=smjcat). SIAM Journal on Computing, 45(5), 1762-1792.
 * Liberty, E. (2013). [Simple and deterministic matrix sketching](http://www.cs.yale.edu/homes/el327/papers/simpleMatrixSketching.pdf). In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 581-588).
+* Teng, D. & Chu, D. (2017). [Low-Rank approximation via sparse frequent directions. arXiv preprint arXiv:1705.07140.](https://arxiv.org/abs/1705.07140)
 
 Contributions
 --------------------------------