map inference

Label Error Correction and Generation through Label Relationships AAAI 2020 MAP Inference for Customized Determinantal Point Processes via Maximum Inner Product Search AISTATS 2020 Online MAP Inference of Determinantal Point Processes NeurIPS 2020 Relative Interior Rule in Block-Coordinate Descent CVPR 2020 Solving Multiple Inference by Minimizing Expected Loss PGM 2020 Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization AISTATS 2020 Block Stability for MAP Inference AISTATS 2019 Bottleneck Potentials in Markov Random Fields ICCV 2019 Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm ICML 2019 Lifted Hinge-Loss Markov Random Fields AAAI 2019 Look Ma, No Latent Variables: Accurate Cutset Networks via Compilation ICML 2019 MAP Inference via Block-Coordinate Frank-Wolfe Algorithm CVPR 2019 One-Shot Marginal MAP Inference in Markov Random Fields UAI 2019 Train and Test Tightness of LP Relaxations in Structured Prediction JMLR 2019 A Novel Approach to Handle Inference in Discrete Markov Networks with Large Label Sets PGM 2018 Continuous Relaxation of MAP Inference: A Nonconvex Perspective CVPR 2018 Fast Greedy MAP Inference for Determinantal Point Process to Improve Recommendation Diversity NeurIPS 2018 Inference in Higher Order MRF-MAP Problems With Small and Large Cliques CVPR 2018 Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time ICML 2018 Markov Random Field MAP as Set Partitioning PGM 2018 Optimality of Approximate Inference Algorithms on Stable Instances AISTATS 2018 Solving M-Modes in Loopy Graphs Using Tree Decompositions PGM 2018 SparseMAP: Differentiable Sparse Structured Inference ICML 2018 A Bayesian Framework for Learning Rule Sets for Interpretable Classification JMLR 2017 Asynchronous Parallel Coordinate Minimization for MAP Inference NeurIPS 2017