Graph Theory

Getting lost in space: Large sample analysis of the resistance distance NeurIPS 2010 Graph Kernels JMLR 2010 Graph-Valued Regression NeurIPS 2010 Identifying graph-structured activation patterns in networks NeurIPS 2010 Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks AISTATS 2010 Kronecker Graphs: An Approach to Modeling Networks JMLR 2010 Learning Networks of Stochastic Differential Equations NeurIPS 2010 Link Discovery using Graph Feature Tracking NeurIPS 2010 Maximum-likelihood learning of cumulative distribution functions on graphs AISTATS 2010 Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes JMLR 2010 Nonparametric Tree Graphical Models AISTATS 2010 Segmentation as Maximum-Weight Independent Set NeurIPS 2010 Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms AISTATS 2010 Subgraph Detection Using Eigenvector L1 Norms NeurIPS 2010 Topology Selection in Graphical Models of Autoregressive Processes JMLR 2010 Using Descendants as Instrumental Variables for the Identification of Direct Causal Effects in Linear SEMs AISTATS 2010 An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity JMLR 2009 Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods JMLR 2009 Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection JMLR 2009 Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation NeurIPS 2009 Human motion database with a binary tree and node transition graphs RSS 2009 Kernels and learning curves for Gaussian process regression on random graphs NeurIPS 2009 Matrix Completion from Power-Law Distributed Samples NeurIPS 2009 The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models JMLR 2009 The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs JMLR 2009