Year |
Citation |
Score |
2019 |
Hosseini R, Sra S. An alternative to EM for Gaussian mixture models: batch and stochastic Riemannian optimization Mathematical Programming. 181: 187-223. DOI: 10.1007/S10107-019-01381-4 |
0.496 |
|
2018 |
Sra S. New concavity and convexity results for symmetric polynomials and their ratios Linear and Multilinear Algebra. 68: 1031-1038. DOI: 10.1080/03081087.2018.1527891 |
0.352 |
|
2016 |
Cherian A, Sra S. Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices. Ieee Transactions On Neural Networks and Learning Systems. PMID 28113681 DOI: 10.1109/Tnnls.2016.2601307 |
0.372 |
|
2016 |
Sra S. On the Matrix Square Root via Geometric Optimization The Electronic Journal of Linear Algebra. 31: 433-443. DOI: 10.13001/1081-3810.3196 |
0.45 |
|
2016 |
Hosseini R, Sra S, Theis L, Bethge M. Inference and mixture modeling with the Elliptical Gamma Distribution Computational Statistics and Data Analysis. 101: 29-43. DOI: 10.1016/J.Csda.2016.02.009 |
0.466 |
|
2015 |
Sra S, Hosseini R. Conic Geometric Optimization on the Manifold of Positive Definite Matrices Siam Journal On Optimization. 25: 713-739. DOI: 10.1137/140978168 |
0.406 |
|
2015 |
Berndt W, Sra S. Hlawka-Popoviciu inequalities on positive definite tensors Linear Algebra and Its Applications. 486: 317-327. DOI: 10.1016/J.Laa.2015.08.028 |
0.301 |
|
2015 |
Mariet Z, Sra S. Fixed-point algorithms for learning determinantal point processes 32nd International Conference On Machine Learning, Icml 2015. 3: 2379-2387. |
0.339 |
|
2014 |
Cherian A, Sra S, Morellas V, Papanikolopoulos N. Efficient nearest neighbors via robust sparse hashing. Ieee Transactions On Image Processing : a Publication of the Ieee Signal Processing Society. 23: 3646-55. PMID 25122742 DOI: 10.1109/Tip.2014.2324280 |
0.322 |
|
2014 |
Yu AW, Ma W, Yu Y, Carbonell JG, Sra S. Efficient structured matrix rank minimization Advances in Neural Information Processing Systems. 2: 1350-1358. |
0.321 |
|
2014 |
Azadi S, Sra S. Towards an optimal stochastic alternating direction method of multipliers 31st International Conference On Machine Learning, Icml 2014. 2: 944-959. |
0.344 |
|
2014 |
Wytock M, Sra S, Kolter JZ. Fast Newton methods for the group fused lasso Uncertainty in Artificial Intelligence - Proceedings of the 30th Conference, Uai 2014. 888-897. |
0.419 |
|
2013 |
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: 2161-74. PMID 23868777 DOI: 10.1109/Tpami.2012.259 |
0.446 |
|
2013 |
Alaíz CM, Dinuzzo F, Sra S. Correlation matrix nearness and completion under observation uncertainty Ima Journal of Numerical Analysis. 35: 325-340. DOI: 10.1093/Imanum/Drt056 |
0.491 |
|
2013 |
Kim D, Sra S, Dhillon IS. A non-monotonic method for large-scale non-negative least squares Optimization Methods and Software. 28: 1012-1039. DOI: 10.1080/10556788.2012.656368 |
0.67 |
|
2013 |
Sra S. Explicit eigenvalues of certain scaled trigonometric matrices Linear Algebra and Its Applications. 438: 173-181. DOI: 10.1016/J.Laa.2012.07.024 |
0.333 |
|
2013 |
Sra S, Karp D. The multivariate watson distribution: Maximum-likelihood estimation and other aspects Journal of Multivariate Analysis. 114: 256-269. DOI: 10.1016/J.Jmva.2012.08.010 |
0.365 |
|
2013 |
Sra S, Hosseini R. Geometric optimisation on positive definite matrices with application to elliptically contoured distributions Advances in Neural Information Processing Systems. |
0.326 |
|
2012 |
Sra S. Fast projections onto mixed-norm balls with applications Data Mining and Knowledge Discovery. 25: 358-377. DOI: 10.1007/S10618-012-0277-7 |
0.44 |
|
2012 |
Sra S. A short note on parameter approximation for von Mises-Fisher distributions: And a fast implementation of I s(x) Computational Statistics. 27: 177-190. DOI: 10.1007/S00180-011-0232-X |
0.4 |
|
2012 |
Sra S. Scalable nonconvex inexact proximal splitting Advances in Neural Information Processing Systems. 1: 530-538. |
0.354 |
|
2011 |
Barbero Á, Sra S. Fast Newton-type methods for total variation regularization Proceedings of the 28th International Conference On Machine Learning, Icml 2011. 313-320. |
0.362 |
|
2010 |
Kim D, Sra S, Dhillon IS. Tackling box-constrained optimization via a new projected quasi-newton approach Siam Journal On Scientific Computing. 32: 3548-3563. DOI: 10.1137/08073812X |
0.66 |
|
2010 |
Harmeling S, Sra S, Hirsch M, Scḧolkopf B. Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM Proceedings - International Conference On Image Processing, Icip. 3313-3316. DOI: 10.1109/ICIP.2010.5651650 |
0.301 |
|
2010 |
Kim D, Sra S, Dhillon I. A scalable trust-region algorithm with application to mixed-norm regression Icml 2010 - Proceedings, 27th International Conference On Machine Learning. 519-526. |
0.42 |
|
2009 |
Kulis B, Sra S, Dhillon I. Convex perturbations for scalable semidefinite programming Journal of Machine Learning Research. 5: 296-303. |
0.344 |
|
2008 |
Sra S. Block-iterative algorithms for non-negative matrix approximation Proceedings - Ieee International Conference On Data Mining, Icdm. 1037-1042. DOI: 10.1109/ICDM.2008.77 |
0.483 |
|
2008 |
Kim D, Sra S, Dhillon IS. Fast projection-based methods for the least squares nonnegative matrix approximation problem Statistical Analysis and Data Mining. 1: 38-51. DOI: 10.1002/Sam.V1:1 |
0.684 |
|
2007 |
Davis JV, Kulis B, Jain P, Sra S, Dhillon IS. Information-theoretic metric learning Acm International Conference Proceeding Series. 227: 209-216. DOI: 10.1145/1273496.1273523 |
0.629 |
|
2007 |
Kim D, Sra S, Dhillon IS. Fast newton-type methods for the least squares nonnegative matrix approximation problem Proceedings of the 7th Siam International Conference On Data Mining. 343-354. |
0.657 |
|
2006 |
Sra S, Tropp JA. Row-action methods for compressed sensing Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 3: III868-III871. |
0.537 |
|
2006 |
Sra S. Efficient large scale linear programming support vector machines Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4212: 767-774. |
0.353 |
|
2005 |
Dhillon IS, Sra S, Tropp JA. Triangle fixing algorithms for the metric nearness problem Advances in Neural Information Processing Systems. |
0.671 |
|
2005 |
Banerjee A, Dhillon IS, Ghosh J, Sra S. Clustering on the unit hypersphere using von Mises-Fisher distributions Journal of Machine Learning Research. 6. |
0.557 |
|
2005 |
Dhillon IS, Sra S. Generalized nonnegative matrix approximations with Bregman divergences Advances in Neural Information Processing Systems. 283-290. |
0.526 |
|
2004 |
Cho H, Dhillon IS, Guan Y, Sra S. Minimum sum-squared residue co-clustering of gene expression data Siam Proceedings Series. 114-125. |
0.564 |
|
2003 |
Banerjee A, Dhillon I, Ghosh J, Sra S. Generative model-based clustering of directional data Proceedings of the Acm Sigkdd International Conference On Knowledge Discovery and Data Mining. 19-28. DOI: 10.1145/956750.956757 |
0.302 |
|
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