دنبال کردن
Nathan Srebro
Nathan Srebro
Professor, TTIC and University of Chicago
ایمیل تأیید شده در ttic.edu
عنوان
نقل شده توسط
نقل شده توسط
سال
Equality of opportunity in supervised learning‏
M Hardt, E Price, N Srebro‏
Advances in neural information processing systems 29, 2016‏
53792016
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
28962007
Exploring generalization in deep learning‏
B Neyshabur, S Bhojanapalli, D McAllester, N Srebro‏
Advances in neural information processing systems 30, 2017‏
15372017
Maximum-margin matrix factorization‏
N Srebro, J Rennie, T Jaakkola‏
Advances in neural information processing systems 17, 2004‏
14312004
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
13812017
Fast maximum margin matrix factorization for collaborative prediction‏
JDM Rennie, N Srebro‏
Proceedings of the 22nd international conference on Machine learning, 713-719, 2005‏
13192005
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
10532018
Weighted low-rank approximations‏
N Srebro, T Jaakkola‏
Proceedings of the 20th international conference on machine learning (ICML …, 2003‏
10482003
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
7682014
Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm‏
D Needell, R Ward, N Srebro‏
Advances in neural information processing systems 27, 2014‏
7362014
A pac-bayesian approach to spectrally-normalized margin bounds for neural networks‏
B Neyshabur, S Bhojanapalli, N Srebro‏
arXiv preprint arXiv:1707.09564, 2017‏
7152017
Norm-based capacity control in neural networks‏
B Neyshabur, R Tomioka, N Srebro‏
Conference on learning theory, 1376-1401, 2015‏
6882015
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
6512018
Learnability, stability and uniform convergence‏
S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan‏
The Journal of Machine Learning Research 11, 2635-2670, 2010‏
5902010
Implicit regularization in matrix factorization‏
S Gunasekar, BE Woodworth, S Bhojanapalli, B Neyshabur, N Srebro‏
Advances in neural information processing systems 30, 2017‏
5722017
Characterizing implicit bias in terms of optimization geometry‏
S Gunasekar, J Lee, D Soudry, N Srebro‏
International Conference on Machine Learning, 1832-1841, 2018‏
5022018
Rank, trace-norm and max-norm‏
N Srebro, A Shraibman‏
International conference on computational learning theory, 545-560, 2005‏
4902005
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
4762018
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
4662016
Learning non-discriminatory predictors‏
B Woodworth, S Gunasekar, MI Ohannessian, N Srebro‏
Conference on learning theory, 1920-1953, 2017‏
4592017
سیستم در حال حاضر قادر به انجام عملکرد نیست. بعداً دوباره امتحان کنید.
مقاله‌ها 1–20