Graphical Models

Sensor Selection in High-Dimensional Gaussian Trees with Nuisances NeurIPS 2013 Similarity Component Analysis NeurIPS 2013 Solving the multi-way matching problem by permutation synchronization NeurIPS 2013 Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting ICML 2013 Sparse Inverse Covariance Estimation with Calibration NeurIPS 2013 Spectral Learning of Hidden Markov Models from Dynamic and Static Data ICML 2013 Statistical Textural Distinctiveness for Salient Region Detection in Natural Images CVPR 2013 Stochastic blockmodel approximation of a graphon: Theory and consistent estimation NeurIPS 2013 Stochastic blockmodeling of relational event dynamics AISTATS 2013 Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization ICML 2013 The Bigraphical Lasso ICML 2013 The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited NeurIPS 2013 Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization CVPR 2013 Tracking Time-varying Graphical Structure NeurIPS 2013 Why Steiner-tree type algorithms work for community detection AISTATS 2013 Σ-Optimality for Active Learning on Gaussian Random Fields NeurIPS 2013 A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation NeurIPS 2012 A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation NeurIPS 2012 Algorithms for Learning Markov Field Policies NeurIPS 2012 Approximate Inference by Intersecting Semidefinite Bound and Local Polytope AISTATS 2012 Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation AISTATS 2012 Augment-and-Conquer Negative Binomial Processes NeurIPS 2012 Bayesian nonparametric models for bipartite graphs NeurIPS 2012 Bayesian Pedigree Analysis using Measure Factorization NeurIPS 2012 Clustering Sparse Graphs NeurIPS 2012