Nathan Srebro
Nathan Srebro
Professor, TTIC and University of Chicago
Verified email at ttic.edu
TitleCited byYear
Pegasos: Primal estimated sub-gradient solver for svm
S Shalev-Shwartz, Y Singer, N Srebro, A Cotter
Mathematical programming 127 (1), 3-30, 2011
20372011
Maximum-margin matrix factorization
N Srebro, J Rennie, TS Jaakkola
Advances in neural information processing systems, 1329-1336, 2005
10382005
Fast maximum margin matrix factorization for collaborative prediction
JDM Rennie, N Srebro
Proceedings of the 22nd international conference on Machine learning, 713-719, 2005
9852005
Weighted low-rank approximations
N Srebro, T Jaakkola
Proceedings of the 20th International Conference on Machine Learning (ICML c, 2003
7622003
Equality of opportunity in supervised learning
M Hardt, E Price, N Srebro
Advances in neural information processing systems, 3315-3323, 2016
5472016
Uncovering shared structures in multiclass classification
Y Amit, M Fink, N Srebro, S Ullman
Proceedings of the 24th international conference on Machine learning, 17-24, 2007
3162007
Rank, trace-norm and max-norm
N Srebro, A Shraibman
International Conference on Computational Learning Theory, 545-560, 2005
3062005
SVM optimization: inverse dependence on training set size
S Shalev-Shwartz, N Srebro
Proceedings of the 25th international conference on Machine learning, 928-935, 2008
2702008
The marginal value of adaptive gradient methods in machine learning
AC Wilson, R Roelofs, M Stern, N Srebro, B Recht
Advances in Neural Information Processing Systems, 4148-4158, 2017
2472017
Learning with matrix factorizations
N Srebro
2072004
Learnability, stability and uniform convergence
S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan
Journal of Machine Learning Research 11 (Oct), 2635-2670, 2010
2032010
Better mini-batch algorithms via accelerated gradient methods
A Cotter, O Shamir, N Srebro, K Sridharan
Advances in neural information processing systems, 1647-1655, 2011
1982011
Global optimality of local search for low rank matrix recovery
S Bhojanapalli, B Neyshabur, N Srebro
Advances in Neural Information Processing Systems, 3873-3881, 2016
1952016
Exploring generalization in deep learning
B Neyshabur, S Bhojanapalli, D McAllester, N Srebro
Advances in Neural Information Processing Systems, 5947-5956, 2017
1922017
A theory of learning with similarity functions
MF Balcan, A Blum, N Srebro
Machine Learning 72 (1-2), 89-112, 2008
1892008
Collaborative filtering in a non-uniform world: Learning with the weighted trace norm
N Srebro, RR Salakhutdinov
Advances in Neural Information Processing Systems, 2056-2064, 2010
1822010
Stochastic gradient descent, weighted sampling, and the randomized kaczmarz algorithm
D Needell, R Ward, N Srebro
Advances in neural information processing systems, 1017-1025, 2014
1722014
Communication-efficient distributed optimization using an approximate newton-type method
O Shamir, N Srebro, T Zhang
International conference on machine learning, 1000-1008, 2014
1712014
Stochastic Convex Optimization.
S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan
COLT, 2009
1672009
Mini-Batch Primal and Dual Methods for SVMs.
M Takác, AS Bijral, P Richtárik, N Srebro
ICML (3), 1022-1030, 2013
1572013
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