Niyogi, Partha

24 publications

JMLR 2013 Manifold Regularization and Semi-Supervised Learning: Some Theoretical Analyses Partha Niyogi

JMLR 2009 Generalization Bounds for Ranking Algorithms via Algorithmic Stability Shivani Agarwal, Partha Niyogi

COLT 2009 On the Sample Complexity of Learning Smooth Cuts on a Manifold Hariharan Narayanan, Partha Niyogi

NeurIPS 2006 Convergence of Laplacian Eigenmaps Mikhail Belkin, Partha Niyogi

JMLR 2006 Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples Mikhail Belkin, Partha Niyogi, Vikas Sindhwani

COLT 2006 Mercer's Theorem, Feature Maps, and Smoothing Ha Quang Minh, Partha Niyogi, Yuan Yao

NeurIPS 2006 On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts Hariharan Narayanan, Mikhail Belkin, Partha Niyogi

ICML 2005 Beyond the Point Cloud: From Transductive to Semi-Supervised Learning Vikas Sindhwani, Partha Niyogi, Mikhail Belkin

NeurIPS 2005 Laplacian Score for Feature Selection Xiaofei He, Deng Cai, Partha Niyogi

AISTATS 2005 On Manifold Regularization Misha Belkin, Partha Niyogi, Vikas Sindhwani

COLT 2005 Stability and Generalization of Bipartite Ranking Algorithms Shivani Agarwal, Partha Niyogi

NeurIPS 2005 Tensor Subspace Analysis Xiaofei He, Deng Cai, Partha Niyogi

COLT 2005 Towards a Theoretical Foundation for Laplacian-Based Manifold Methods Mikhail Belkin, Partha Niyogi

COLT 2004 Regularization and Semi-Supervised Learning on Large Graphs Mikhail Belkin, Irina Matveeva, Partha Niyogi

MLJ 2004 Semi-Supervised Learning on Riemannian Manifolds Mikhail Belkin, Partha Niyogi

NeCo 2003 Laplacian Eigenmaps for Dimensionality Reduction and Data Representation Mikhail Belkin, Partha Niyogi

NeurIPS 2003 Locality Preserving Projections Xiaofei He, Partha Niyogi

UAI 2002 Almost-Everywhere Algorithmic Stability and Generalization Error Samuel Kutin, Partha Niyogi

NeurIPS 2002 Using Manifold Stucture for Partially Labeled Classification Mikhail Belkin, Partha Niyogi

NeurIPS 2001 Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering Mikhail Belkin, Partha Niyogi

ICML 2000 An Approach to Data Reduction and Clustering with Theoretical Guarantees Partha Niyogi, Narendra Karmarkar

NeCo 1996 On the Relationship Between Generalization Error, Hypothesis Complexity, and Sample Complexity for Radial Basis Functions Partha Niyogi, Federico Girosi

ICML 1995 Free to Choose: Investigating the Sample Complexity of Active Learning of Real Valued Functions Partha Niyogi

NeurIPS 1994 Active Learning for Function Approximation Kah Kay Sung, Partha Niyogi