ising model

Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay NeurIPS 2019 Inference and Sampling of K_33-free Ising Models ICML 2019 Ising Models with Latent Conditional Gaussian Variables ALT 2019 Learning Ising Models with Independent Failures COLT 2019 Learning Tree Structures from Noisy Data AISTATS 2019 Lower bounds for testing graphical models: colorings and antiferromagnetic Ising models COLT 2019 Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models NeurIPS 2019 Structure Learning with Side Information: Sample Complexity NeurIPS 2019 Deep Learning the Ising Model Near Criticality JMLR 2018 Optimal Single Sample Tests for Structured versus Unstructured Network Data COLT 2018 Sparse Estimation in Ising Model via Penalized Monte Carlo Methods JMLR 2018 The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity COLT 2018 The Vertex Sample Complexity of Free Energy is Polynomial COLT 2018 Annular Augmentation Sampling AISTATS 2017 A Screening Rule for l1-Regularized Ising Model Estimation NeurIPS 2017 Concentration of Multilinear Functions of the Ising Model with Applications to Network Data NeurIPS 2017 Improving Gibbs Sampler Scan Quality with DoGS ICML 2017 Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications NeurIPS 2017 Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models AISTATS 2017 Removing Phase Transitions from Gibbs Measures AISTATS 2017 Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods NeurIPS 2016 Bayesian Generalised Ensemble Markov Chain Monte Carlo AISTATS 2016 Generalized Direct Change Estimation in Ising Model Structure ICML 2016 How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods COLT 2016 Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models NeurIPS 2016