עקוב אחר
Nathan Srebro
Nathan Srebro
Professor, TTIC and University of Chicago
כתובת אימייל מאומתת בדומיין ttic.edu
כותרת
צוטט על ידי
צוטט על ידי
שנה
Equality of opportunity in supervised learning
M Hardt, E Price, N Srebro
Advances in neural information processing systems 29, 2016
43902016
Pegasos: Primal estimated sub-gradient solver for svm
S Shalev-Shwartz, Y Singer, N Srebro
Proceedings of the 24th international conference on Machine learning, 807-814, 2007
28232007
Maximum-margin matrix factorization
N Srebro, J Rennie, T Jaakkola
Advances in neural information processing systems 17, 2004
14022004
Exploring generalization in deep learning
B Neyshabur, S Bhojanapalli, D McAllester, N Srebro
Advances in neural information processing systems 30, 2017
13002017
Fast maximum margin matrix factorization for collaborative prediction
JDM Rennie, N Srebro
Proceedings of the 22nd international conference on Machine learning, 713-719, 2005
12932005
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 30, 2017
12292017
Weighted low-rank approximations
N Srebro, T Jaakkola
Proceedings of the 20th international conference on machine learning (ICML …, 2003
10252003
The implicit bias of gradient descent on separable data
D Soudry, E Hoffer, MS Nacson, S Gunasekar, N Srebro
Journal of Machine Learning Research 19 (70), 1-57, 2018
8972018
Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm
D Needell, R Ward, N Srebro
Advances in neural information processing systems 27, 2014
6702014
In search of the real inductive bias: On the role of implicit regularization in deep learning
B Neyshabur, R Tomioka, N Srebro
arXiv preprint arXiv:1412.6614, 2014
6672014
A pac-bayesian approach to spectrally-normalized margin bounds for neural networks
B Neyshabur, S Bhojanapalli, N Srebro
arXiv preprint arXiv:1707.09564, 2017
6222017
Norm-based capacity control in neural networks
B Neyshabur, R Tomioka, N Srebro
Conference on learning theory, 1376-1401, 2015
5982015
Towards understanding the role of over-parametrization in generalization of neural networks
B Neyshabur, Z Li, S Bhojanapalli, Y LeCun, N Srebro
arXiv preprint arXiv:1805.12076, 2018
5722018
Learnability, stability and uniform convergence
S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan
The Journal of Machine Learning Research 11, 2635-2670, 2010
5162010
Implicit regularization in matrix factorization
S Gunasekar, BE Woodworth, S Bhojanapalli, B Neyshabur, N Srebro
Advances in neural information processing systems 30, 2017
4972017
Rank, trace-norm and max-norm
N Srebro, A Shraibman
International conference on computational learning theory, 545-560, 2005
4792005
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
4302016
Implicit bias of gradient descent on linear convolutional networks
S Gunasekar, JD Lee, D Soudry, N Srebro
Advances in neural information processing systems 31, 2018
4172018
Characterizing implicit bias in terms of optimization geometry
S Gunasekar, J Lee, D Soudry, N Srebro
International Conference on Machine Learning, 1832-1841, 2018
4132018
Learning non-discriminatory predictors
B Woodworth, S Gunasekar, MI Ohannessian, N Srebro
Conference on Learning Theory, 1920-1953, 2017
4082017
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מאמרים 1–20