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Suvrit Sra, Dr. (Univ. Texas at Austin; USA)

Address:	Spemannstr. 38 72076 Tübingen
Room number:	214
Phone:	+49 7071 601 572
Fax:	+49 7071 601 552
E-Mail:	suvrit.sra

Picture of Sra, Suvrit, Dr. (Univ. Texas at Austin; USA)

Suvrit Sra

Position: Research Scientist Unit: Alumni Schölkopf

Overview
Publications

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Books (1):
•	Sra S , Nowozin S and Wright SJ : Optimization for Machine Learning, 494, MIT Press, Cambridge, MA, USA, (December-2011). ISBN: 978-0-262-01646-9
Articles (7):
•	Cherian A , Sra S , Banerjee A and Papanikolopoulos N (May-2012) Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices IEEE Transactions on Pattern Analysis and Machine Intelligence . submitted
•	Sra S (March-2012) A short note on parameter approximation for von Mises-Fisher distributions: and a fast implementation of Is(x) Computational Statistics 27(1) 177-190.
•	Hirsch M , Harmeling S , Sra S and Schölkopf B (July-2011) Online Multi-frame Blind Deconvolution with Super-resolution and Saturation Correction Astronomy & Astrophysics 531(A9) 11 pages.
•	Kim D , Sra S and Dhillon IS (December-2010) Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach SIAM Journal on Scientific Computing 32(6) 3548-3563.
•	Brickell J , Dhillon IS , Sra S and Tropp JA (April-2008) The Metric Nearness Problem SIAM Journal on Matrix Analysis and Applications 30(1) 375-396.
•	Kim D , Sra S and Dhillon I (February-2008) Fast Projection-based Methods for the Least Squares Nonnegative Matrix Approximation Problem Statistical Analysis and Data Mining 1(1) 38-51.
•	Banerjee A , Dhillon I , Ghosh J and Sra S (September-2005) Clustering on the Unit Hypersphere using von Mises-Fisher Distributions Journal of Machine Learning Research 6 1345-1382.
Conference papers (19):
•	Langovoy M and Sra S (December-2011) Statistical estimation for optimization problems on graphs NIPS Workshop on Discrete Optimization in Machine Learning (DISCML) 2011: Uncertainty, Generalization and Feedback, 1-6.
•	Harmeling S , Sra S , Hirsch M and Schölkopf B (September-2010) Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction via Incremental EM 17th International Conference on Image Processing (ICIP 2010), IEEE, Piscataway, NJ, USA, 3313-3316.
•	Kim D , Sra S and Dhillon I (June-2010) A scalable trust-region algorithm with application to mixed-norm regression 27th International Conference on Machine Learning (ICML 2010), International Machine Learning Society, Madison, WI, USA, 519-526.
•	Hirsch M , Sra S , Schölkopf B and Harmeling S (June-2010) Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), IEEE, Piscataway, NJ, USA, 607-614.
•	Sra S , Kim D , Dhillon I and Schölkopf B (October-2009) A new non-monotonic algorithm for PET image reconstruction In: NSS/MIC 2009, IEEE Nuclear Science Symposium Conference Record, IEEE, Piscataway, NJ, USA, 2009, 2500-2502.
•	Jegelka S , Sra S and Banerjee A (October-2009) Approximation Algorithms for Tensor Clustering In: ALT 2009, The 20th International Conference on Algorithmic Learning Theory, Springer, Berlin, Germany, 368-383.
•	Kulis B , Sra S and Dhillon I (April-2009) Convex Perturbations for Scalable Semidefinite Programming In: JMLR Workshop and Conference Proceedings Volume 5: AISTATS 2009, Twelfth International Conference on Artificial Intelligence and Statistics, MIT Press, Cambridge, MA, USA, 296-303.
•	Harmeling S , Hirsch M , Sra S and Schölkopf B (April-2009) Online blind deconvolution for astronomical imaging First IEEE International Conference Computational Photography (ICCP 2009), IEEE, Piscataway, NJ, USA, 1-7.
•	Sra S (December-2008) Block Iterative Algorithms for Non-negative Matrix Approximation In: ICDM 2008, Eighth IEEE International Conference on Data Mining, IEEE Service Center, Piscataway, NJ, USA, 1037-1042.
•	Davis JV , Kulis B , Jain P , Sra S and Dhillon IS (June-2007) Information-theoretic Metric Learning In: ICML 2007, 24th Annual International Conference on Machine Learning, ACM Press, New York, NY, USA, 209-216.
•	Kim D , Sra S and Dhillon I (April-2007) Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem In: SDM 2007, SIAM International Conference on Data Mining, Society for Industrial and Applied Mathematics, Pittsburgh, PA, USA, 343-354.
•	Davis J , Kulis B , Sra S and Dhillon I (December-2006) Information-theoretic Metric Learning NIPS 2006 Workshop on Learning to Compare Examples, 1-5.
•	Sra S (September-2006) Efficient Large Scale Linear Programming Support Vector Machines In: ECML 2006, 17th European Conference on Machine Learning, Springer, Berlin, Germany, 767-774.
•	Surendran A and Sra S (September-2006) Incremental Aspect Models for Mining Document Streams In: PKDD 2006, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Springer, Berlin, Germany, 633-640.
•	Dhillon I and Sra S (May-2006) Generalized Nonnegative Matrix Approximations with Bregman Divergences In: Advances in neural information processing systems 18, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), MIT Press, Cambridge, MA, USA, 283-290.
•	Sra S and Tropp J (May-2006) Row-Action Methods for Compressed Sensing In: ICASSP 2006, IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE Operations Center, Piscataway, NJ, USA, 868-871.
•	Dhillon I , Sra S and Tropp J (July-2005) Triangle Fixing Algorithms for the Metric Nearness Problem In: Advances in Neural Information Processing Systems 17, Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), MIT Press, Cambridge, MA, USA, 361-368.
•	Cho H , Guan Y , Dhillon I and Sra S (April-2004) Minimum Sum-Squared Residue based clustering of Gene Expression Data SDM 2004, 00-00.
•	Banerjee A , Dhillon I , Ghosh J and Sra S (August-2003) Generative Model-based Clustering of Directional Data KDD 2003, 00-00.
Contributions to books (2):
•	Schmidt M , Kim D and Sra S : Projected Newton-type methods in machine learning, 305-330. In: Optimization for Machine Learning, (Ed) S. Sra, MIT Press, Cambridge, MA, USA, (December-2011).
•	Sra S , Banerjee A , Ghosh J and Dhillon I : Text Clustering with Mixture of von Mises-Fisher Distributions, 121-161. In: Text mining: classification, clustering, and applications, (Ed) A. N. Srivastava, CRC Press, Boca Raton, FL, USA, (June-2009).
Technical reports (18):
•	Tandon R and Sra S : Sparse nonnegative matrix approximation: new formulations and algorithms, 193, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (September-2010).
•	Barbero Jimenez A and Sra S : Fast algorithms for total-variation based optimization, 194, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (August-2010).
•	Sra S : Generalized Proximity and Projection with Norms and Mixed-norms, 192, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (May-2010).
•	Harmeling S , Sra S , Hirsch M and Schölkopf B : An Incremental GEM Framework for Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction, 187, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (November-2009).
•	Hirsch M , Sra S , Schölkopf B and Harmeling S : Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution, 188, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (November-2009).
•	Sra S , Jegelka S and Banerjee A : Approximation Algorithms for Bregman Clustering Co-clustering and Tensor Clustering, 177, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, (September-2008).
•	Sra S : Block-Iterative Algorithms for Non-Negative Matrix Approximation, 176, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, (September-2008).
•	Kim D , Sra S and Dhillon I : A New Non-monotonic Gradient Projection Method for the Non-negative Least Squares Problem, TR-08-28, University of Texas, Austin, TX, USA, (June-2008).
•	Sra S , Kim D and Schölkopf B : Non-monotonic Poisson Likelihood Maximization, 170, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, (June-2008).
•	Kulis B , Sra S and Jegelka S : Scalable Semidefinite Programming using Convex Perturbations, TR-07-47, University of Texas, Austin, TX, USA, (September-2007).
•	Sra S , Jain P and Dhillon I : Modeling data using directional distributions: Part II, TR-07-05, University of Texas, Austin, TX, USA, (February-2007).
•	Kim D , Sra S and Dhillon I : A New Projected Quasi-Newton Approach for the Nonnegative Least Squares Problem, TR-06-54, Univ. of Texas, Austin, (December-2006).
•	Sra S and Dhillon I : Nonnegative Matrix Approximation: Algorithms and Applications, Univ. of Texas, Austin, (May-2006).
•	Sra S and Dhillon I : Generalized Nonnegative Matrix Approximations using Bregman Divergences, Univ. of Texas at Austin, (June-2005).
•	Dhillon I , Sra S and Tropp J : Triangle Fixing Algorithms for the Metric Nearness Problem, Univ. of Texas at Austin, (June-2004).
•	Dhillon I , Sra S and Tropp J : The Metric Nearness Problem with Applications, Univ. of Texas at Austin, (June-2003).
•	Banerjee A , Dhillon I , Ghosh J and Sra S : Expectation Maximization for Clustering on Hyperspheres, Univ. of Texas at Austin, (February-2003).
•	Dhillon I and Sra S : Modeling Data using Directional Distributions, Univ. of Texas at Austin, (January-2003).
Posters (3):
•	Sra S (June-2010): Solving large-scale nonnegative least-squares, 16th Conference of the International Linear Algebra Society (ILAS 2010), 16 19.
•	Sra S , Kim D and Dhillon I (April-2010): Solving large-scale nonnegative least squares using an adaptive non-monotonic method, 24th European Conference on Operational Research (EURO 2010), 24 223.
•	Kim D , Sra S and Dhillon I (April-2010): Sparse regression via a trust-region proximal method, 24th European Conference on Operational Research (EURO 2010), 24 278.