Mikhail (Misha) Belkin

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Vikas SindhwaniRobotics at Google, New YorkVerified email at google.com
Yusu WangProfessor, HDSI, Univ. California, San Diego.Verified email at ucsd.edu
Siyuan MaThe Ohio State UniversityVerified email at cse.ohio-state.edu
Daniel HsuColumbia UniversityVerified email at cs.columbia.edu
Ulrike von LuxburgUniversity of TübingenVerified email at informatik.uni-tuebingen.de
Luis RademacherDepartment of Mathematics, UC DavisVerified email at math.ucdavis.edu
James VossGoogleVerified email at google.com
Olivier BousquetGoogleVerified email at m4x.org
Simon DennisProfessor, University of MelbourneVerified email at unimelb.edu.au
Kaushik SinhaWichita State UniversityVerified email at wichita.edu
Jihun HammTulane UniversityVerified email at tulane.edu
jian sunProfessor, Tsinghua UniversityVerified email at math.tsinghua.edu.cn
Justin EldridgePhD Student, Computer Science, The Ohio State UniversityVerified email at cse.ohio-state.edu
Lorenzo RosascoMaLGa Machine Learning Genoa Center - Università degli Studi di GenovaVerified email at mit.edu
Ernesto De VitoMaLGa Machine Learning Genoa Center - Università di GenovaVerified email at unige.it
Qichao QueFacebookVerified email at fb.com
Xueyuan ZhouPhD, Computer Science, University of ChicagoVerified email at cs.uchicago.edu
Stefano MelacciAssociate Professor, University of Siena, ItalyVerified email at diism.unisi.it
Chaoyue Liuthe Ohio State UniversityVerified email at osu.edu
Raef BassilyAssistant Professor, Computer Science & Engineering, The Ohio State UniversityVerified email at osu.edu

Mikhail (Misha) Belkin

Professor of Data Science, Halıcıoğlu Data Science Institute, UCSD

Verified email at ucsd.edu - Homepage

Machine Learning Learning Theory Artificial Intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Laplacian eigenmaps for dimensionality reduction and data representation M Belkin, P Niyogi Neural computation 15 (6), 1373-1396, 2003	8027	2003
Laplacian eigenmaps and spectral techniques for embedding and clustering. M Belkin, P Niyogi Nips 14 (14), 585-591, 2001	4873	2001
Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. M Belkin, P Niyogi, V Sindhwani Journal of machine learning research 7 (11), 2006	4088	2006
Semi-supervised learning on Riemannian manifolds M Belkin, P Niyogi Machine learning 56 (1), 209-239, 2004	944	2004
Regularization and semi-supervised learning on large graphs M Belkin, I Matveeva, P Niyogi International Conference on Computational Learning Theory, 624-638, 2004	689	2004
Towards a theoretical foundation for Laplacian-based manifold methods M Belkin, P Niyogi Journal of Computer and System Sciences 74 (8), 1289-1308, 2008	584	2008
Consistency of spectral clustering U Von Luxburg, M Belkin, O Bousquet The Annals of Statistics, 555-586, 2008	582	2008
Beyond the point cloud: from transductive to semi-supervised learning V Sindhwani, P Niyogi, M Belkin Proceedings of the 22nd international conference on Machine learning, 824-831, 2005	550	2005
Reconciling modern machine-learning practice and the classical bias–variance trade-off M Belkin, D Hsu, S Ma, S Mandal Proceedings of the National Academy of Sciences 116 (32), 15849-15854, 2019, 2019	463	2019
A co-regularization approach to semi-supervised learning with multiple views V Sindhwani, P Niyogi, M Belkin Proceedings of ICML workshop on learning with multiple views 2005, 74-79, 2005	438	2005
Laplacian support vector machines trained in the primal S Melacci, M Belkin Journal of Machine Learning Research 12 (31), 1149−1184, 2011	360	2011
On Manifold Regularization. M Belkin, P Niyogi, V Sindhwani AISTATS, 2005	352	2005
Using Manifold Structure for Partially Labeled Classification M Belkin, P Niyogi NIPS 2002, 2003	344	2003
Convergence of Laplacian eigenmaps M Belkin, P Niyogi Advances in Neural Information Processing Systems 19, 129, 2007	272	2007
Discrete Laplace operator on meshed surfaces M Belkin, J Sun, Y Wang Proceedings of the twenty-fourth annual symposium on Computational geometry …, 2008	250	2008
Polynomial learning of distribution families M Belkin, K Sinha SIAM Journal on Computing 44 (4), 889-911, 2015	213	2015
Constructing Laplace Operator from Point Clouds in ℝ^d M Belkin, J Sun, Y Wang Proceedings of the twentieth annual ACM-SIAM symposium on Discrete …, 2009	188	2009
On learning with integral operators. L Rosasco, M Belkin, E De Vito Journal of Machine Learning Research 11 (2), 2010	183	2010
To understand deep learning we need to understand kernel learning M Belkin, S Ma, S Mandal The 35th International Conference on Machine Learning (ICML 2018), 2018	182	2018
Problems of learning on manifolds M Belkin University of Chicago, Dept. of Mathematics, 2003	176	2003

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