| Year | Citation | Score | |||
|---|---|---|---|---|---|
| 2014 | Wang J, Srebro N, Evans J. Active collaborative permutation learning Proceedings of the Acm Sigkdd International Conference On Knowledge Discovery and Data Mining. 502-511. DOI: 10.1145/2623330.2623730 | 0.569 | |||
| 2014 | Shamir O, Srebro N. Distributed stochastic optimization and learning 2014 52nd Annual Allerton Conference On Communication, Control, and Computing, Allerton 2014. 850-857. DOI: 10.1109/ALLERTON.2014.7028543 | 0.498 | |||
| 2013 | Sabato S, Srebro N, Tishby N. Distribution-dependent sample complexity of large margin learning Journal of Machine Learning Research. 14: 2119-2149. | 0.592 | |||
| 2013 | Cotter A, Srebro N, Shalev-Shwartz S. Learning optimally sparse support vector machines 30th International Conference On Machine Learning, Icml 2013. 266-274. | 0.418 | |||
| 2013 | Sabato S, Sarwate AD, Srebro N. Auditing: Active learning with outcome-dependent query costs Advances in Neural Information Processing Systems. | 0.396 | |||
| 2011 | Hazan E, Koren T, Srebro N. Beating SGD: Learning SVMs in sublinear time Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011. | 0.576 | |||
| 2011 | Foygel R, Salakhutdinov R, Shamir O, Srebro N. Learning with the weighted trace-norm under arbitrary sampling distributions Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011. | 0.56 | |||
| 2011 | Zhou X, Srebro N. Error analysis of laplacian eigenmaps for semi-supervised learning Journal of Machine Learning Research. 15: 901-908. | 0.474 | |||
| 2011 | Bijral AS, Ratliff N, Srebro N. Semi-supervised learning with density based distances Proceedings of the 27th Conference On Uncertainty in Artificial Intelligence, Uai 2011. 43-60. | 0.516 | |||
| 2010 | Salakhutdinov R, Srebro N. Collaborative filtering in a non-uniform world: Learning with the weighted trace norm Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. | 0.379 | |||
| 2010 | Liang P, Srebro N. On the interaction between norm and dimensionality: Multiple regimes in learning Icml 2010 - Proceedings, 27th International Conference On Machine Learning. 647-654. | 0.521 | |||
| 2010 | Sabato S, Srebro N, Tishby N. Reducing label complexity by learning from bags Journal of Machine Learning Research. 9: 685-692. | 0.575 | |||
| 2010 | Sabato S, Srebro N, Tishby N. Tight sample complexity of large-margin learning Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. | 0.601 | |||
| 2009 | Shalev-Shwartz S, Shamir O, Srebro N, Sridharan K. Learnability and stability in the general learning setting Colt 2009 - the 22nd Conference On Learning Theory. | 0.504 | |||
| 2009 | Nadler B, Srebro N, Zhou X. Semi-supervised learning with the graph laplacian: The limit of infinite unlabelled data Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 1331-1338. | 0.451 | |||
| 2008 | Balcan MF, Blum A, Srebro N. A theory of learning with similarity functions Machine Learning. 72: 89-112. DOI: 10.1007/S10994-008-5059-5 | 0.329 | |||
| 2008 | Balcan MF, Blum A, Srebro N. Improved guarantees for learning via similarity functions 21st Annual Conference On Learning Theory, Colt 2008. 287-298. | 0.548 | |||
| 2006 | Srebro N, Ben-David S. Learning bounds for support vector machines with learned kernels Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4005: 169-183. | 0.56 | |||
| 2001 | Karger D, Srebro N. Learning Markov networks: Maximum bounded tree-width graphs Proceedings of the Annual Acm-Siam Symposium On Discrete Algorithms. 392-401. | 0.371 | |||
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