Graphical Models

BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables NeurIPS 2013 Bilinear Programming for Human Activity Recognition with Unknown MRF Graphs CVPR 2013 Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels ACML 2013 Collective Stability in Structured Prediction: Generalization from One Example ICML 2013 Computing the M Most Probable Modes of a Graphical Model AISTATS 2013 Conditional Random Fields via Univariate Exponential Families NeurIPS 2013 Contextual Hypergraph Modeling for Salient Object Detection ICCV 2013 Continuous Inference in Graphical Models with Polynomial Energies CVPR 2013 Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs ICML 2013 Diffusion Processes for Retrieval Revisited CVPR 2013 Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests NeurIPS 2013 Discrete MRF Inference of Marginal Densities for Non-uniformly Discretized Variable Space CVPR 2013 Discriminative Label Propagation for Multi-object Tracking with Sporadic Appearance Features ICCV 2013 EDML for Learning Parameters in Directed and Undirected Graphical Models NeurIPS 2013 Embed and Project: Discrete Sampling with Universal Hashing NeurIPS 2013 Exemplar Cut ICCV 2013 Exploring the Mind: Integrating Questionnaires and fMRI ICML 2013 GeoF: Geodesic Forests for Learning Coupled Predictors CVPR 2013 Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation NeurIPS 2013 Graphical Models for Inference with Missing Data NeurIPS 2013 Hierarchical Tensor Decomposition of Latent Tree Graphical Models ICML 2013 Incremental Semantically Grounded Learning from Demonstration RSS 2013 In Defense of 3D-Label Stereo CVPR 2013 Inference algorithms for pattern-based CRFs on sequence data ICML 2013 Inferring neural population dynamics from multiple partial recordings of the same neural circuit NeurIPS 2013