Mikhail Belkin

	2011
35		Xueyuan Zhou, Mikhail Belkin, Nathan Srebro: An iterated graph laplacian approach for ranking on manifolds. KDD 2011: 877-885
34		Xiaoyin Ge, Issam Safa, Mikhail Belkin, Yusu Wang: Data Skeletonization via Reeb Graphs. NIPS 2011: 837-845
33		Xueyuan Zhou, Mikhail Belkin: Behavior of Graph Laplacians on Manifolds with Boundary CoRR abs/1105.3931: (2011)
32		Stefano Melacci, Mikhail Belkin: Laplacian Support Vector Machines Trained in the Primal. Journal of Machine Learning Research 12: 1149-1184 (2011)
31		Xueyuan Zhou, Mikhail Belkin: Semi-supervised Learning by Higher Order Regularization. Journal of Machine Learning Research - Proceedings Track 15: 892-900 (2011)
	2010
30		Mikhail Belkin, Kaushik Sinha: Toward Learning Gaussian Mixtures with Arbitrary Separation. COLT 2010: 407-419
29		Mikhail Belkin, Kaushik Sinha: Polynomial Learning of Distribution Families. FOCS 2010: 103-112
28		Andrew R. Plummer, Mary E. Beckman, Mikhail Belkin, Eric Fosler-Lussier, Benjamin Munson: Learning speaker normalization using semisupervised manifold alignment. INTERSPEECH 2010: 2918-2921
27		Mikhail Belkin, Kaushik Sinha: Polynomial Learning of Distribution Families CoRR abs/1004.4864: (2010)
26		Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito: On Learning with Integral Operators. Journal of Machine Learning Research 11: 905-934 (2010)
	2009
25		Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito: A Note on Learning with Integral Operators. COLT 2009
24		Kaushik Sinha, Mikhail Belkin: Semi-supervised Learning using Sparse Eigenfunction Bases. NIPS 2009: 1687-1695
23		Mikhail Belkin, Jian Sun, Yusu Wang: Constructing Laplace operator from point clouds in Rd. SODA 2009: 1031-1040
22		Mikhail Belkin, Kaushik Sinha: Learning Gaussian Mixtures with Arbitrary Separation CoRR abs/0907.1054: (2009)
	2008
21		Tao Shi, Mikhail Belkin, Bin Yu: Data spectroscopy: learning mixture models using eigenspaces of convolution operators. ICML 2008: 936-943
20		Lei Ding, Mikhail Belkin: Probabilistic mixtures of differential profiles for shape recognition. ICPR 2008: 1-4
19		Lei Ding, Mikhail Belkin: Component based shape retrieval using differential profiles. Multimedia Information Retrieval 2008: 216-222
18		Mikhail Belkin, Jian Sun, Yusu Wang: Discrete laplace operator on meshed surfaces. Symposium on Computational Geometry 2008: 278-287
17		Mikhail Belkin, Partha Niyogi: Towards a theoretical foundation for Laplacian-based manifold methods. J. Comput. Syst. Sci. 74(8): 1289-1308 (2008)
	2007
16		Kaushik Sinha, Mikhail Belkin: The Value of Labeled and Unlabeled Examples when the Model is Imperfect. NIPS 2007
	2006
15		Mikhail Belkin, Hariharan Narayanan, Partha Niyogi: Heat Flow and a Faster Algorithm to Compute the Surface Area of a Convex Body. FOCS 2006: 47-56
14		Hariharan Narayanan, Mikhail Belkin, Partha Niyogi: On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts. NIPS 2006: 1025-1032
13		Mikhail Belkin, Partha Niyogi: Convergence of Laplacian Eigenmaps. NIPS 2006: 129-136
12		Mikhail Belkin, Partha Niyogi, Vikas Sindhwani: Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples. Journal of Machine Learning Research 7: 2399-2434 (2006)
	2005
11		Mikhail Belkin, Partha Niyogi: Towards a Theoretical Foundation for Laplacian-Based Manifold Methods. COLT 2005: 486-500
10		Vikas Sindhwani, Partha Niyogi, Mikhail Belkin: Beyond the point cloud: from transductive to semi-supervised learning. ICML 2005: 824-831
9		Yasemin Altun, David A. McAllester, Mikhail Belkin: Margin Semi-Supervised Learning for Structured Variables. NIPS 2005
	2004
8		Ulrike von Luxburg, Olivier Bousquet, Mikhail Belkin: On the Convergence of Spectral Clustering on Random Samples: The Normalized Case. COLT 2004: 457-471
7		Mikhail Belkin, Irina Matveeva, Partha Niyogi: Regularization and Semi-supervised Learning on Large Graphs. COLT 2004: 624-638
6		Ulrike von Luxburg, Olivier Bousquet, Mikhail Belkin: Limits of Spectral Clustering. NIPS 2004
5		Mikhail Belkin, Partha Niyogi: Semi-Supervised Learning on Riemannian Manifolds. Machine Learning 56(1-3): 209-239 (2004)
	2003
4		Mikhail Belkin, Partha Niyogi: Laplacian Eigenmaps for Dimensionality Reduction and Data Representation. Neural Computation 15(6): 1373-1396 (2003)
	2002
3		Mikhail Belkin, Partha Niyogi: Using Manifold Stucture for Partially Labeled Classification. NIPS 2002: 929-936
2		Mikhail Belkin, John A. Goldsmith: Using eigenvectors of the bigram graph to infer morpheme identity CoRR cs.CL/0207002: (2002)
	2001
1		Mikhail Belkin, Partha Niyogi: Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering. NIPS 2001: 585-591

Coauthor Index

1	Yasemin Altun	[9]
2	Mary E. Beckman	[28]
3	Olivier Bousquet	[6] [8]
4	Lei Ding	[19] [20]
5	Eric Fosler-Lussier	[28]
6	Xiaoyin Ge	[34]
7	John A. Goldsmith	[2]
8	Ulrike von Luxburg	[6] [8]
9	Irina Matveeva	[7]
10	David A. McAllester	[9]
11	Stefano Melacci	[32]
12	Benjamin Munson	[28]
13	Hariharan Narayanan	[14] [15]
14	Partha Niyogi	[1] [3] [4] [5] [7] [10] [11] [12] [13] [14] [15] [17]
15	Andrew R. Plummer	[28]
16	Lorenzo Rosasco	[25] [26]
17	Issam Safa	[34]
18	Tao Shi	[21]
19	Vikas Sindhwani	[10] [12]
20	Kaushik Sinha	[16] [22] [24] [27] [29] [30]
21	Nathan Srebro (Nati Srebro)	[35]
22	Jian Sun	[18] [23]
23	Ernesto De Vito	[25] [26]
24	Yusu Wang	[18] [23] [34]
25	Bin Yu	[21]
26	Xueyuan Zhou	[31] [33] [35]

Colors in the list of coauthors

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