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

Adresse: Spemannstr. 38
72076 Tübingen
Raum Nummer: 214

 

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Suvrit Sra

Position: Wissenschaftler  Abteilung: 

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Bücher (1):

Sra S, Nowozin S und Wright SJ: Optimization for Machine Learning, 494, MIT Press, Cambridge, MA, USA, (Dezember-2011). ISBN: 978-0-262-01646-9, Series: Neural information processing series

Artikel (9):

Hosseini R, Sra S, Theis L und Bethge M (September-2016) Inference and mixture modeling with the Elliptical Gamma Distribution Computational Statistics & Data Analysis 101 29–43.
Hosseini R, Sra S, Theis L und Bethge M (Oktober-2014) Statistical inference with the Elliptical Gamma Distribution Machine Learning . eingereicht
Cherian A, Sra S, Banerjee A und Papanikolopoulos N (September-2013) Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices IEEE Transactions on Pattern Analysis and Machine Intelligence 35(9) 2161-2174.
Sra S (März-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.
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Hirsch M, Harmeling S, Sra S und Schölkopf B (Juli-2011) Online Multi-frame Blind Deconvolution with Super-resolution and Saturation Correction Astronomy & Astrophysics 531(A9) 11 pages.
Kim D, Sra S und Dhillon IS (Dezember-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 und Tropp JA (April-2008) The Metric Nearness Problem SIAM Journal on Matrix Analysis and Applications 30(1) 375-396.
Kim D, Sra S und Dhillon I (Februar-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 und Sra S (September-2005) Clustering on the Unit Hypersphere using von Mises-Fisher Distributions Journal of Machine Learning Research 6 1345-1382.

Beiträge zu Tagungsbänden (23):

Sra S, Hosseini R, Theis L und Bethge M (Mai-2015) Data modeling with the elliptical gamma distribution, 18th International Conference on Artificial Intelligence and Statistics (AISTATS 2015), International Machine Learning Society, Madison, WI, USA, 903–911, Series: JMLR Workshop and Conference Proceedings ; 38.
Sra S und Hosseini R (2014) Geometric optimisation on positive definite matrices with application to elliptically contoured distributions In: Advances in Neural Information Processing Systems 26, , Twenty-Seventh Annual Conference on Neural Information Processing Systems (NIPS 2013), Curran, Red Hook, NY, USA, 2564-2572.
Langovoy M und Sra S (Dezember-2011) Statistical estimation for optimization problems on graphs, NIPS Workshop on Discrete Optimization in Machine Learning (DISCML 2011): Uncertainty, Generalization and Feedback, 1-6.
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Cherian A, Sra S und Papanikolopoulos N (Mai-2011) Denoising sparse noise via online dictionary learning, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), IEEE, Piscataway, NJ, USA, 2060-2063.
Harmeling S, Sra S, Hirsch M und 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.
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Kim D, Sra S und Dhillon I (Juni-2010) A scalable trust-region algorithm with application to mixed-norm regression, 27th International Conference on Machine Learning (ICML 2010), Curran, Red Hook, NY, USA, 519-526.
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Hirsch M, Sra S, Schölkopf B und Harmeling S (Juni-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.
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Sra S, Kim D, Dhillon I und Schölkopf B (Oktober-2009) A new non-monotonic algorithm for PET image reconstruction In: Nuclear Science Symposium Conference Record, , IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC 2009), IEEE, Piscataway, NJ, USA, 2500-2502.
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Jegelka S, Sra S und Banerjee A (Oktober-2009) Approximation Algorithms for Tensor Clustering In: Algorithmic Learning Theory, , 20th International Conference on Algorithmic Learning Theory (ALT 2009), Springer, Berlin, Germany, 368-383, Series: Lecture Notes in Computer Science ; 5809.
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Kulis B, Sra S und Dhillon I (April-2009) Convex Perturbations for Scalable Semidefinite Programming, Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS 2009), International Machine Learning Society, Madison, WI, USA, 296-303, Series: JMLR Workshop and Conference Proceedings ; 5.
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Harmeling S, Hirsch M, Sra S und Schölkopf B (April-2009) Online blind deconvolution for astronomical imaging, First IEEE International Conference Computational Photography (ICCP 2009), IEEE, Piscataway, NJ, USA, 1-7.
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Sra S (Dezember-2008) Block Iterative Algorithms for Non-negative Matrix Approximation, 8th IEEE International Conference on Data Mining (ICDM 2008), IEEE Service Center, Piscataway, NJ, USA, 1037-1042.
Sra S (Dezember-2008) Block-iterative algorithms for non-negative matrix approximation, 8th IEEE International Conference on Data Mining (ICDM 2008), IEEE, Piscataway, NJ, USA, 1037-1042.
Davis JV, Kulis B, Jain P, Sra S und Dhillon IS (Juni-2007) Information-theoretic Metric Learning, 24th Annual International Conference on Machine Learning (ICML 2007), ACM Press, New York, NY, USA, 209-216.
Kim D, Sra S und Dhillon I (April-2007) Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem, Seventh SIAM International Conference on Data Mining (SDM 2007), Society for Industrial and Applied Mathematics, Pittsburgh, PA, USA, 343-354.
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Davis J, Kulis B, Sra S und Dhillon I (Dezember-2006) Information-theoretic Metric Learning, NIPS 2006 Workshop on Learning to Compare Examples, NIPS 2006 Workshop on Learning to Compare Examples, 1-5.
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Sra S (September-2006) Efficient Large Scale Linear Programming Support Vector Machines In: Machine Learning: ECML 2006, , 17th European Conference on Machine Learning, Springer, Berlin, Germany, 767-774, Series: Lecture Notes in Computer Science ; 4212.
Surendran A und Sra S (September-2006) Incremental Aspect Models for Mining Document Streams In: Knowledge Discovery in Databases: PKDD 2006, , 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Springer, Berlin, Germany, 633-640, Series: Lecture Notes in Computer Science ; 4213.
Dhillon I und Sra S (Mai-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.
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Sra S und Tropp J (Mai-2006) Row-Action Methods for Compressed Sensing, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), IEEE Operations Center, Piscataway, NJ, USA, 868-871.
Dhillon I, Sra S und Tropp J (Juli-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.
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Cho H, Guan Y, Dhillon I und Sra S (April-2004) Minimum Sum-Squared Residue based Co-clustering of Gene Expression Data, Fourth SIAM International Conference on Data Mining (SDM 2004), Society for Industrial and Applied Mathematics, Pittsburgh, PA, USA, 114-125.
Banerjee A, Dhillon I, Ghosh J und Sra S (August-2003) Generative Model-based Clustering of Directional Data, KDD 2003, Proc. ACK SIGKDD, 00-00.

Beiträge zu Büchern (2):

Schmidt M, Kim D und Sra S: Projected Newton-type methods in machine learning, 305-330. In: Optimization for Machine Learning, (Ed) S. Sra, MIT Press, Cambridge, MA, USA, (Dezember-2011).
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Sra S, Banerjee A, Ghosh J und 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, (Juni-2009).

Technische Berichte (18):

Tandon R und Sra S: Sparse nonnegative matrix approximation: new formulations and algorithms, 193, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (September-2010).
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Barbero Jimenez A und Sra S: Fast algorithms for total-variation based optimization, 194, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (August-2010).
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Sra S: Generalized Proximity and Projection with Norms and Mixed-norms, 192, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (Mai-2010).
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Harmeling S, Sra S, Hirsch M und 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).
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Hirsch M, Sra S, Schölkopf B und Harmeling S: Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution, 188, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (November-2009).
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Sra S, Jegelka S und Banerjee A: Approximation Algorithms for Bregman Clustering Co-clustering and Tensor Clustering, 177, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, (September-2008).
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Sra S: Block-Iterative Algorithms for Non-Negative Matrix Approximation, 176, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, (September-2008).
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Kim D, Sra S und 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, (Juni-2008).
Sra S, Kim D und Schölkopf B: Non-monotonic Poisson Likelihood Maximization, 170, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, (Juni-2008).
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Kulis B, Sra S und Jegelka S: Scalable Semidefinite Programming using Convex Perturbations, TR-07-47, University of Texas, Austin, TX, USA, (September-2007).
Sra S, Jain P und Dhillon I: Modeling data using directional distributions: Part II, TR-07-05, University of Texas, Austin, TX, USA, (Februar-2007).
Kim D, Sra S und Dhillon I: A New Projected Quasi-Newton Approach for the Nonnegative Least Squares Problem, TR-06-54, Univ. of Texas, Austin, (Dezember-2006).
Sra S und Dhillon I: Nonnegative Matrix Approximation: Algorithms and Applications, Univ. of Texas, Austin, (Mai-2006).
Sra S und Dhillon I: Generalized Nonnegative Matrix Approximations using Bregman Divergences, Univ. of Texas at Austin, (Juni-2005).
Dhillon I, Sra S und Tropp J: Triangle Fixing Algorithms for the Metric Nearness Problem, Univ. of Texas at Austin, (Juni-2004).
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Last updated: Montag, 22.05.2017