Publications of S Sra

Report (17)

41.
Report
Barbero Jimenez, A.; Sra, S.: Fast algorithms for total-variation based optimization (Technical Report of the Max Planck Institute for Biological Cybernetics, 194). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2010), 27 pp.
42.
Report
Sra, S.: Generalized Proximity and Projection with Norms and Mixed-norms (Technical Report of the Max Planck Institute for Biological Cybernetics, 192). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2010), 13 pp.
43.
Report
Harmeling, S.; Sra, S.; Hirsch, M.; Schölkopf, B.: An Incremental GEM Framework for Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction (Technical Report of the Max Planck Institute for Biological Cybernetics, 187). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2009), 9 pp.
44.
Report
Hirsch, M.; Sra, S.; Schölkopf, B.; Harmeling, S.: Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution (Technical Report of the Max Planck Institute for Biological Cybernetics, 188). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2009), 9 pp.
45.
Report
Sra, S.: Block-Iterative Algorithms for Non-Negative Matrix Approximation (Technical Report of the Max Planck Institute for Biological Cybernetics, 176). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 16 pp.
46.
Report
Sra, S.; Jegelka, S.; Banerjee, A.: Approximation Algorithms for Bregman Clustering Co-clustering and Tensor Clustering (Technical Report of the Max Planck Institute for Biological Cybernetics, 177). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 21 pp.
47.
Report
Kim, D.; Sra, S.; Dhillon, I.: A New Non-monotonic Gradient Projection Method for the Non-negative Least Squares Problem. University of Texas: Computer Sciences, Austin, TX, USA (2008)
48.
Report
Sra, S.; Kim, D.; Schölkopf, B.: Non-monotonic Poisson Likelihood Maximization (Technical Report of the Max Planck Institute for Biological Cybernetics, 170). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2008), 18 pp.
49.
Report
Kulis, B.; Sra, S.; Jegelka, S.; Dhillon, I.: Scalable Semidefinite Programming using Convex Perturbations. University of Texas, Austin, TX, USA (2007), 14 pp.
50.
Report
Sra, S.; Jain, P.; Dhillon, I.: Modeling data using directional distributions: Part II. University of Texas, Austin, TX, USA (2007), 15 pp.
51.
Report
Kim, D.; Sra, S.; Dhillon, I.: A New Projected Quasi-Newton Approach for the Nonnegative Least Squares Problem. University of Texas, Austin, TX, USA (2006), 16 pp.
52.
Report
Sra, S.; Dhillon, I.: Nonnegative Matrix Approximation: Algorithms and Applications. University of Texas, Austin, TX, USA (2006)
53.
Report
Dhillon, I.; Sra, S.: Generalized Nonnegative Matrix Approximations using Bregman Divergences. Department of Computer Sciences: University of Texas, Austin, TX, USA (2005), 14 pp.
54.
Report
Dhillon, I.; Sra, S.; Tropp, J.: The Metric Nearness Problem with Applications. University of Texas: Department of Computer Science, Austin, TX, USA (2003), 14 pp.
55.
Report
Banerjee, A.; Dhillon, I.; Ghosh, J.; Sra, S.: Expectation Maximization for Clustering on Hyperspheres. University of Texas: Department of Computer Science, Austin, TX, USA (2003), 33 pp.
56.
Report
Dhillon, I.; Sra, S.: Modeling Data using Directional Distributions. University of Texas: Department of Computer Science, Austin, TX, USA (2003), 21 pp.
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