MATH 710-01 [2589], Fall 2015
Mathematics of Big Data

1. selected by Alvaro Arrospide Fletcher on August 27, 2015 to be presented on October 8, 2015
   Principal Direction Divisive Partitioning. Daniel Boley, Data Mining and Knowledge Discovery Volume 2, Issue 4, (1998), pp 325-344.
2. selected by Xiaowei Song on August 27, 2015 to be presented on October 15, 2015
   Presentation.
   Clustering with Bregman Divergences. A. Banerjee, S. Merugu, I. S. Dhillon, and J. Ghosh, Proceedings of the Fourth SIAM International Conference on Data Mining, pages 234-245, April 2004
   • Learning with Bregman Divergences. I. S. Dhillon
   • Total Bregman Divergence and Its Applications to DTI Analysis. Vemuri, B.C., Liu, M., Amari, S.-I., Nielsen, F., 2011. IEEE Transactions on Medical Imaging 30, 475483. doi:10.1109/TMI.2010.2086464
3. selected by Maria Barouti on August 31, 2015 to be presented on October 22, 2015
   Presentation.
   Entropic means. A. Ben-Tal, A.Charnes, M. Teboulle, Journal of Mathematical Analysis and Applications 139 (1989), 537-551.
4. selected by Teresa Lebair on September 3, 2015 to be presented on October 29, 2015
   Presentation.
   Non-exhaustive, overlapping, k-means. Whang, Dhillon, Gleich, SDM 2015.
5. selected by Zois Boukouvalas on September 8, 2015 to be presented on November 5, 2015
   Presentation.
   Clustering for Monitoring Distributed Data Streams. M. Barouti, D. Keren, J. Kogan and Y. Malinovsky, in Partitional Clustering Algorithms, M. Emre Celebi (eds.), Springer, pp. 385-413, 2014.
6. selected by Xinxuan Li on September 27, 2015 to be presented on November 12, 2015
   Presentation and convergence.
   Scalable Data-driven PageRank: Algorithms, System Issues, and Lessons Learned. J. Whang, A. Lenharth, I. Dhillon, K. Pingali.
   In International European Conference on Parallel and Distributed Computing (Euro-Par), pp. 438-450, August 2015.
7. selected by Seyedahmad Mousavi on September 20, 2015 to be presented on November 19, 2015
   Presentation
   A tutorial on spectral clustering. Ulrike von Luxburg, in Statistics and Computing December 2007, Volume 17, Issue 4, pp 395-416
8. selected by Caroline Scheck on September 8, 2015 to be presented on December 3, 2015
   Multi-Scale Spectral Decomposition of Massive Graphs. Si, Shin, Dhillon, Parlett. NIPS 2014.
9. selected by Tim Brown on November 23, 2015 to be presented on December 10, 2015
   Distributional Rank Aggregation, and an Axiomatic Analysis. A. Prasad, H. Pareek, P. Ravikumar. In International Conference on Machine Learning (ICML), July 2015.

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10. Data-based Manifold Reconstruction via Tangent Bundle Manifold Learning. Alexander Bernstein, Alexander Kuleshov.
11. A unified continuous optimization framework for center-based clustering methods. M. Teboulle, Journal of Machine Learning Research, 8, (2007) 65-102
12. Additive Regularization of Topic Models for Topic Selection and Sparse Factorization. Konstantin Vorontsov, Anna Potapenko, Alexander Plavin
    Statistical Learning and Data Sciences, Volume 9047 of the series Lecture Notes in Computer Science (2015), Springer-Verlag, pp 193-202.
13. QUIC & DIRTY : A Quadratic Approximation Approach for Dirty Statistical Models. Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep Ravikumar Stephen Becker, and Peder A. Olsen
14. A New Copula for Modeling Tail Dependence. J. Holman and G. Ritter, November 10, 2010
15. Multiperiod Portfolio Selection and Bayesian Dynamic Models. G. Ritter, 2014.