graph laplacian

The Generalized Laplacian Distance and Its Applications for Visual Matching CVPR 2013 A Local Spectral Method for Graphs: With Applications to Improving Graph Partitions and Exploring Data Graphs Locally JMLR 2012 Constrained 1-Spectral Clustering AISTATS 2012 Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling NeurIPS 2012 Semi-supervised Eigenvectors for Locally-biased Learning NeurIPS 2012 Spectral Clustering of Graphs with General Degrees in the Extended Planted Partition Model COLT 2012 Toward Understanding Complex Spaces: Graph Laplacians on Manifolds with Singularities and Boundaries COLT 2012 Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning AISTATS 2011 Operator Norm Convergence of Spectral Clustering on Level Sets JMLR 2011 Regularized Laplacian Estimation and Fast Eigenvector Approximation NeurIPS 2011 Semi-supervised Learning by Higher Order Regularization AISTATS 2011 Identifying graph-structured activation patterns in networks NeurIPS 2010 On Learning with Integral Operators JMLR 2010 Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming NeurIPS 2009 Manifold Regularization for SIR with Rate Root-n Convergence NeurIPS 2009 Semi-Supervised Learning in Gigantic Image Collections NeurIPS 2009 Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction NeurIPS 2009 Fast Prediction on a Tree NeurIPS 2008 Spectral Hashing NeurIPS 2008 Graph Laplacians and their Convergence on Random Neighborhood Graphs JMLR 2007 Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes JMLR 2007 Statistical Analysis of Semi-Supervised Regression NeurIPS 2007 Graph Laplacian Regularization for Large-Scale Semidefinite Programming NeurIPS 2006 Learning on Graph with Laplacian Regularization NeurIPS 2006 Manifold Denoising NeurIPS 2006