Suchergebnisse

Zeitschriftenartikel (10)

  1. 1.
    Zeitschriftenartikel
    Hosseini, R.; Sra, S.; Theis, L.; Bethge, M.: Inference and mixture modeling with the Elliptical Gamma Distribution. Computational Statistics Data Analysis 101, S. 29 - 43 (2016)
  2. 2.
    Zeitschriftenartikel
    Hosseini, R.; Sra, S.; Theis, L.; Bethge, M.: Statistical inference with the Elliptical Gamma Distribution. Computational Statistics & Data Analysis 101, S. 29 - 43 (2016)
  3. 3.
    Zeitschriftenartikel
    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), S. 2161 - 2174 (2013)
  4. 4.
    Zeitschriftenartikel
    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), S. 2161 - 2174 (2012)
  5. 5.
    Zeitschriftenartikel
    Sra, S.: A short note on parameter approximation for von Mises-Fisher distributions: and a fast implementation of Is(x). Computational Statistics 27 (1), S. 177 - 190 (2012)
  6. 6.
    Zeitschriftenartikel
    Hirsch, M.; Harmeling, S.; Sra, S.; Schölkopf, B.: Online Multi-frame Blind Deconvolution with Super-resolution and Saturation Correction. Astronomy & Astrophysics 531 (A9), S. 1 - 11 (2011)
  7. 7.
    Zeitschriftenartikel
    Kim, D.; Sra, S.; Dhillon, I.: Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach. SIAM Journal on Scientific Computing 32 (6), S. 3548 - 3563 (2010)
  8. 8.
    Zeitschriftenartikel
    Brickell, J.; Dhillon, I.; Sra, S.; Tropp, J.: The Metric Nearness Problem. SIAM journal on matrix analysis and applications 30 (1), S. 375 - 396 (2008)
  9. 9.
    Zeitschriftenartikel
    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), S. 38 - 51 (2008)
  10. 10.
    Zeitschriftenartikel
    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, S. 1345 - 1382 (2005)

Buch (1)

  1. 11.
    Buch
    Sra, S.; Nowozin, S.; Wright, S. (Hg.): Optimization for Machine Learning. MIT Press, Cambridge, MA, USA (2011), 494 S.

Buchkapitel (3)

  1. 12.
    Buchkapitel
    Schmidt, M.; Kim, D.; Sra, S.: Projected Newton-type methods in machine learning. In: Optimization for Machine Learning, S. 305 - 330 (Hg. Sra, S.; Nowozin, S.; Wright, S.). MIT Press, Cambridge, MA, USA (2011)
  2. 13.
    Buchkapitel
    Sra, S.; Nowozin, S.; Wright, S.: Introduction: Optimization and Machine Learning. In: Optimization for Machine Learning, S. 1 - 17 (Hg. Sra, S.; Nowozin, S.; Wright, S.). MIT Press, Cambridge, MA, USA (2011)
  3. 14.
    Buchkapitel
    Banerjee, A.; Ghosh, J.; Dhillon, I.; Sra, S.: Text Clustering with Mixture of von Mises-Fisher Distributions. In: Text mining: classification, clustering, and applications, S. 121 - 154 (Hg. Srivastava, A.; Sahami, M.). CRC Press, Boca Raton, FL, USA (2009)

Konferenzbeitrag (19)

  1. 15.
    Konferenzbeitrag
    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, S. 903 - 911 (Hg. 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)
  2. 16.
    Konferenzbeitrag
    Sra, S.; Hosseini, R.: Geometric optimisation on positive definite matrices with application to elliptically contoured distributions. In: Advances in Neural Information Processing Systems 26, S. 2564 - 2572 (Hg. 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)
  3. 17.
    Konferenzbeitrag
    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, S. 1 - 6. NIPS Workshop on Discrete Optimization in Machine Learning (DISCML) 2011: Uncertainty, Generalization and Feedback. (2011)
  4. 18.
    Konferenzbeitrag
    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), S. 2060 - 2063. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), Praha, Czech Republic, 22. Mai 2011 - 27. Mai 2011. IEEE, Piscataway, NJ, USA (2011)
  5. 19.
    Konferenzbeitrag
    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), S. 3313 - 3316. 17th International Conference on Image Processing (ICIP 2010), Hong Kong, China, 26. September 2010 - 29. September 2010. IEEE, Piscataway, NJ, USA (2010)
  6. 20.
    Konferenzbeitrag
    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), S. 607 - 614. Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, USA, 13. Juni 2010 - 18. Juni 2010. IEEE, Piscataway, NJ, USA (2010)
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