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Graph Theory

1375 directly classified papers

Papers per year

Papers

Structure Learning of Partitioned Markov Networks ICML 2016
Uprooting and Rerooting Graphical Models ICML 2016
Learning Planar Ising Models JMLR 2016
Bayesian Graphical Models for Multivariate Functional Data JMLR 2016
Classification of Imbalanced Data with a Geometric Digraph Family JMLR 2016
Stable Graphical Models JMLR 2016
Joint Structural Estimation of Multiple Graphical Models JMLR 2016
Local Network Community Detection with Continuous Optimization of Conductance and Weighted Kernel K-Means JMLR 2016
Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models JMLR 2016
Exact Inference on Gaussian Graphical Models of Arbitrary Topology using Path-Sums JMLR 2016
Tensor Power Iteration for Multi-Graph Matching CVPR 2016
On Valid Optimal Assignment Kernels and Applications to Graph Classification NIPS 2016
Completely random measures for modelling block-structured sparse networks NIPS 2016
Constraints Based Convex Belief Propagation NIPS 2016
Semiparametric Differential Graph Models NIPS 2016
Data driven estimation of Laplace-Beltrami operator NIPS 2016
The Multiscale Laplacian Graph Kernel NIPS 2016
Clustering Signed Networks with the Geometric Mean of Laplacians NIPS 2016
Linear Shape Deformation Models With Local Support Using Graph-Based Structured Matrix Factorisation CVPR 2016
Memory Efficient Max Flow for Multi-Label Submodular MRFs CVPR 2016
Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation NIPS 2016
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models NIPS 2016
Cooperative Graphical Models NIPS 2016
Optimal Cluster Recovery in the Labeled Stochastic Block Model NIPS 2016
Edge-exchangeable graphs and sparsity NIPS 2016