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Journal Article (10)

1.
Journal Article
Hosseini, R.; Sra, S.; Theis, L.; Bethge, M.: Statistical inference with the Elliptical Gamma Distribution. Computational Statistics & Data Analysis 101, pp. 29 - 43 (2016)
2.
Journal Article
Hosseini, R.; Sra, S.; Theis, L.; Bethge, M.: Inference and mixture modeling with the Elliptical Gamma Distribution. Computational Statistics Data Analysis 101, pp. 29 - 43 (2016)
3.
Journal Article
Cherian, A.; Sra, S.; Banerjee, A.; Papanikolopoulos, N.: Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices. IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (9), pp. 2161 - 2174 (2013)
4.
Journal Article
Cherian, A.; Sra, S.; Banerjee, A.; Papanikolopoulos, N.: Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices. IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (9), pp. 2161 - 2174 (2012)
5.
Journal Article
Sra, S.: A short note on parameter approximation for von Mises-Fisher distributions: and a fast implementation of Is(x). Computational Statistics 27 (1), pp. 177 - 190 (2012)
6.
Journal Article
Hirsch, M.; Harmeling, S.; Sra, S.; Schölkopf, B.: Online Multi-frame Blind Deconvolution with Super-resolution and Saturation Correction. Astronomy & Astrophysics 531 (A9), pp. 1 - 11 (2011)
7.
Journal Article
Kim, D.; Sra, S.; Dhillon, I.: Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach. SIAM Journal on Scientific Computing 32 (6), pp. 3548 - 3563 (2010)
8.
Journal Article
Brickell, J.; Dhillon, I.; Sra, S.; Tropp, J.: The Metric Nearness Problem. SIAM journal on matrix analysis and applications 30 (1), pp. 375 - 396 (2008)
9.
Journal Article
Kim, D.; Sra, S.; Dhillon, I.: Fast Projection-based Methods for the Least Squares Nonnegative Matrix Approximation Problem. Statistical Analysis and Data Mining 1 (1), pp. 38 - 51 (2008)
10.
Journal Article
Banerjee, A.; Dhillon , I.; Ghosh, J.; Sra, S.: Clustering on the Unit Hypersphere using von Mises-Fisher Distributions. The Journal of Machine Learning Research 6, pp. 1345 - 1382 (2005)

Book (1)

11.
Book
Sra, S.; Nowozin, S.; Wright, S. (Eds.): Optimization for Machine Learning. MIT Press, Cambridge, MA, USA (2011), 494 pp.

Book Chapter (3)

12.
Book Chapter
Schmidt, M.; Kim, D.; Sra, S.: Projected Newton-type methods in machine learning. In: Optimization for Machine Learning, pp. 305 - 330 (Eds. Sra, S.; Nowozin, S.; Wright, S.). MIT Press, Cambridge, MA, USA (2011)
13.
Book Chapter
Sra, S.; Nowozin, S.; Wright, S.: Introduction: Optimization and Machine Learning. In: Optimization for Machine Learning, pp. 1 - 17 (Eds. Sra, S.; Nowozin, S.; Wright, S.). MIT Press, Cambridge, MA, USA (2011)
14.
Book Chapter
Banerjee, A.; Ghosh, J.; Dhillon, I.; Sra, S.: Text Clustering with Mixture of von Mises-Fisher Distributions. In: Text mining: classification, clustering, and applications, 6, pp. 121 - 154 (Eds. Srivastava, A.; Sahami, M.). CRC Press, Boca Raton, FL, USA (2009)

Conference Paper (19)

15.
Conference Paper
Sra, S.; Hosseini, R.; Theis, L.; Bethge, M.: Data modeling with the elliptical gamma distribution. In: Artificial Intelligence and Statistics, 9-12 May 2015, San Diego, California, USA, pp. 903 - 911 (Eds. Lebanon, G.; Vishwanathan, S.). 18th International Conference on Artificial Intelligence and Statistics (AISTATS 2015), San Diego, CA, USA. International Machine Learning Society, Madison, WI, USA (2015)
16.
Conference Paper
Sra, S.; Hosseini, R.: Geometric optimisation on positive definite matrices with application to elliptically contoured distributions. In: Advances in Neural Information Processing Systems 26, pp. 2564 - 2572 (Eds. Burges, C.; Bottou, L.; Welling, M.; Ghahramani, Z.). Twenty-Seventh Annual Conference on Neural Information Processing Systems (NIPS 2013), Stateline, NV, USA. Curran, Red Hook, NY, USA (2014)
17.
Conference Paper
Langovoy, M.; Sra, S.: Statistical estimation for optimization problems on graphs. In: NIPS Workshop on Discrete Optimization in Machine Learning (DISCML) 2011: Uncertainty, Generalization and Feedback, pp. 1 - 6. NIPS Workshop on Discrete Optimization in Machine Learning (DISCML) 2011: Uncertainty, Generalization and Feedback. (2011)
18.
Conference Paper
Cherian, A.; Sra, S.; Papanikolopoulos, N.: Denoising sparse noise via online dictionary learning. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), pp. 2060 - 2063. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), Praha, Czech Republic, May 22, 2011 - May 27, 2011. IEEE, Piscataway, NJ, USA (2011)
19.
Conference Paper
Harmeling, S.; Sra, S.; Hirsch, M.; Schölkopf, B.: Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction via Incremental EM. In: 17th International Conference on Image Processing (ICIP 2010), pp. 3313 - 3316. 17th International Conference on Image Processing (ICIP 2010), Hong Kong, China, September 26, 2010 - September 29, 2010. IEEE, Piscataway, NJ, USA (2010)
20.
Conference Paper
Hirsch, M.; Sra, S.; Schölkopf, B.; Harmeling, S.: Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution. In: Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), pp. 607 - 614. Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, USA, June 13, 2010 - June 18, 2010. IEEE, Piscataway, NJ, USA (2010)
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