high-dimensional inference

High-Dimensional Gaussian Process Inference with Derivatives ICML 2021 Inference for the Case Probability in High-dimensional Logistic Regression JMLR 2021 Inference In High-dimensional Single-Index Models Under Symmetric Designs JMLR 2021 Online stochastic gradient descent on non-convex losses from high-dimensional inference JMLR 2021 On the difficulty of unbiased alpha divergence minimization ICML 2021 Scalable Inference in SDEs by Direct Matching of the Fokker–Planck–Kolmogorov Equation NeurIPS 2021 Sliced Mutual Information: A Scalable Measure of Statistical Dependence NeurIPS 2021 SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression NeurIPS 2021 Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon AISTATS 2021 High-Dimensional Inference for Cluster-Based Graphical Models JMLR 2020 Projected Stein Variational Gradient Descent NeurIPS 2020 Sharp Asymptotics and Optimal Performance for Inference in Binary Models AISTATS 2020 Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso NeurIPS 2020 High Dimensional Inference in Partially Linear Models AISTATS 2019 LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations ICML 2019 Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions NeurIPS 2019 Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models COLT 2018 Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models JMLR 2018 Scaling the Poisson GLM to massive neural datasets through polynomial approximations NeurIPS 2018 Simultaneous Clustering and Estimation of Heterogeneous Graphical Models JMLR 2018 Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference ICML 2017 An equivalence between high dimensional Bayes optimal inference and M-estimation NeurIPS 2016 Inference for High-dimensional Exponential Family Graphical Models AISTATS 2016 High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality NeurIPS 2015 High-dimensional Inference via Lipschitz Sparsity-Yielding Regularizers AISTATS 2013