Nathan Srebro

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	总计	2018 年至今
引用	31072	21907
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i10 指数	155	136

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Shai Shalev-ShwartzThe Hebrew University在 cs.huji.ac.il 的电子邮件经过验证
Behnam NeyshaburSenior Staff Research Scientist, DeepMind在 google.com 的电子邮件经过验证
Karthik SridharanCornell University, University of Pennsylvania, Toyota Technological Institute在 ttic.edu 的电子邮件经过验证
Ohad ShamirWeizmann Institute of Science在 weizmann.ac.il 的电子邮件经过验证
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton University在 princeton.edu 的电子邮件经过验证
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMU在 cs.cmu.edu 的电子邮件经过验证
Jason RennieSoftware Engieer, Google在 google.com 的电子邮件经过验证
Benjamin RechtProfessor of EECS, University of California, Berkeley在 eecs.berkeley.edu 的电子邮件经过验证
Avrim BlumProfessor and Chief Academic Officer, Toyota Technological Institute at Chicago在 ttic.edu 的电子邮件经过验证
Ambuj Tewari | अम्बुज तिवारीProfessor, Statistics and EECS, University of Michigan在 umich.edu 的电子邮件经过验证
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Xueyuan ZhouPhD, Computer Science, University of Chicago在 cs.uchicago.edu 的电子邮件经过验证
Erik DemaineProfessor of Electrical Engineering and Computer Science, Massachusetts Institute of Technology在 mit.edu 的电子邮件经过验证
Rachel Ward在 math.utexas.edu 的电子邮件经过验证
Martin TakáčMohamed bin Zayed University of Artificial Intelligence (MBZUAI)在 mbzuai.ac.ae 的电子邮件经过验证
Andreas ArgyriouMicrosoft UK在 alum.mit.edu 的电子邮件经过验证
Shai Ben-DavidUniverity of Waterloo, Canada在 uwaterloo.ca 的电子邮件经过验证
David KargerProfessor of Computer Science, MIT在 mit.edu 的电子邮件经过验证
Deanna NeedellProfessor of Mathematics, UCLA在 cmc.edu 的电子邮件经过验证
Sam Roweis (Memorial)New York University在 buffalo.edu 的电子邮件经过验证

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Nathan Srebro

Professor, TTIC and University of Chicago

在 ttic.edu 的电子邮件经过验证

Machine Learning Statistical Learning Theory


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Equality of opportunity in supervised learning M Hardt, E Price, N Srebro Advances in neural information processing systems 29, 2016	3871	2016
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	2770	2007
Maximum-margin matrix factorization N Srebro, J Rennie, T Jaakkola Advances in neural information processing systems 17, 2004	1386	2004
Fast maximum margin matrix factorization for collaborative prediction JDM Rennie, N Srebro Proceedings of the 22nd international conference on Machine learning, 713-719, 2005	1278	2005
Exploring generalization in deep learning B Neyshabur, S Bhojanapalli, D McAllester, N Srebro Advances in neural information processing systems 30, 2017	1189	2017
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	1155	2017
Weighted low-rank approximations N Srebro, T Jaakkola Proceedings of the 20th international conference on machine learning (ICML …, 2003	1003	2003
The implicit bias of gradient descent on separable data D Soudry, E Hoffer, MS Nacson, S Gunasekar, N Srebro The Journal of Machine Learning Research 19 (1), 2822-2878, 2018	834	2018
Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm D Needell, R Ward, N Srebro Advances in neural information processing systems 27, 2014	627	2014
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	615	2014
A pac-bayesian approach to spectrally-normalized margin bounds for neural networks B Neyshabur, S Bhojanapalli, N Srebro arXiv preprint arXiv:1707.09564, 2017	583	2017
Norm-based capacity control in neural networks B Neyshabur, R Tomioka, N Srebro Conference on learning theory, 1376-1401, 2015	567	2015
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	541	2018
Learnability, stability and uniform convergence S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan The Journal of Machine Learning Research 11, 2635-2670, 2010	488	2010
Rank, trace-norm and max-norm N Srebro, A Shraibman International conference on computational learning theory, 545-560, 2005	468	2005
Implicit regularization in matrix factorization S Gunasekar, BE Woodworth, S Bhojanapalli, B Neyshabur, N Srebro Advances in neural information processing systems 30, 2017	436	2017
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	413	2016
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	401	2007
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	380	2018
Learning non-discriminatory predictors B Woodworth, S Gunasekar, MI Ohannessian, N Srebro Conference on Learning Theory, 1920-1953, 2017	375	2017

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