Nathan Srebro

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Shai Shalev-ShwartzThe Hebrew UniversityEmail yang diverifikasi di cs.huji.ac.il
Behnam NeyshaburSenior Staff Research Scientist, DeepMindEmail yang diverifikasi di google.com
Karthik SridharanCornell University, University of Pennsylvania, Toyota Technological InstituteEmail yang diverifikasi di ttic.edu
Ohad ShamirWeizmann Institute of ScienceEmail yang diverifikasi di weizmann.ac.il
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton UniversityEmail yang diverifikasi di princeton.edu
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUEmail yang diverifikasi di cs.cmu.edu
Jason RennieSoftware Engieer, GoogleEmail yang diverifikasi di google.com
Benjamin RechtProfessor of EECS, University of California, BerkeleyEmail yang diverifikasi di eecs.berkeley.edu
Avrim BlumProfessor and Chief Academic Officer, Toyota Technological Institute at ChicagoEmail yang diverifikasi di ttic.edu
Ambuj Tewari | अम्बुज तिवारीProfessor, Statistics and EECS, University of MichiganEmail yang diverifikasi di umich.edu
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon UniversityEmail yang diverifikasi di cs.cmu.edu
Xueyuan ZhouPhD, Computer Science, University of ChicagoEmail yang diverifikasi di cs.uchicago.edu
Rachel WardUT Austin / Microsoft ResearchEmail yang diverifikasi di math.utexas.edu
Erik DemaineProfessor of Electrical Engineering and Computer Science, Massachusetts Institute of TechnologyEmail yang diverifikasi di mit.edu
Martin TakáčMohamed bin Zayed University of Artificial Intelligence (MBZUAI)Email yang diverifikasi di mbzuai.ac.ae
Andreas ArgyriouMicrosoft UKEmail yang diverifikasi di alum.mit.edu
Shai Ben-DavidUniverity of Waterloo, CanadaEmail yang diverifikasi di uwaterloo.ca
David KargerProfessor of Computer Science, MITEmail yang diverifikasi di mit.edu
Deanna NeedellProfessor of Mathematics, UCLAEmail yang diverifikasi di cmc.edu
Sam Roweis (Memorial)New York UniversityEmail yang diverifikasi di buffalo.edu

Ikuti

Nathan Srebro

Professor, TTIC and University of Chicago

Email yang diverifikasi di ttic.edu

Machine Learning Statistical Learning Theory


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Equality of opportunity in supervised learning M Hardt, E Price, N Srebro Advances in neural information processing systems 29, 2016	5095	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	2888	2007
Exploring generalization in deep learning B Neyshabur, S Bhojanapalli, D McAllester, N Srebro Advances in neural information processing systems 30, 2017	1465	2017
Maximum-margin matrix factorization N Srebro, J Rennie, T Jaakkola Advances in neural information processing systems 17, 2004	1433	2004
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	1334	2017
Fast maximum margin matrix factorization for collaborative prediction JDM Rennie, N Srebro Proceedings of the 22nd international conference on Machine learning, 713-719, 2005	1318	2005
Weighted low-rank approximations N Srebro, T Jaakkola Proceedings of the 20th international conference on machine learning (ICML …, 2003	1040	2003
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	1025	2018
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	740	2014
Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm D Needell, R Ward, N Srebro Advances in neural information processing systems 27, 2014	712	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	685	2017
Norm-based capacity control in neural networks B Neyshabur, R Tomioka, N Srebro Conference on learning theory, 1376-1401, 2015	663	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	620	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	564	2010
Implicit regularization in matrix factorization S Gunasekar, BE Woodworth, S Bhojanapalli, B Neyshabur, N Srebro Advances in neural information processing systems 30, 2017	556	2017
Rank, trace-norm and max-norm N Srebro, A Shraibman International conference on computational learning theory, 545-560, 2005	488	2005
Characterizing implicit bias in terms of optimization geometry S Gunasekar, J Lee, D Soudry, N Srebro International Conference on Machine Learning, 1832-1841, 2018	476	2018
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	462	2018
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	459	2016
Learning non-discriminatory predictors B Woodworth, S Gunasekar, MI Ohannessian, N Srebro Conference on Learning Theory, 1920-1953, 2017	450	2017

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