gaussian approximation

Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation UAI 2026 Gaussian Approximation for Two-Timescale Linear Stochastic Approximation AAAI 2026 Online Detection of Changes in Moment--Based Projections: When to Retrain Deep Learners or Update Portfolios? JMLR 2026 Batch, match, and patch: low-rank approximations for score-based variational inference AISTATS 2025 Streamlining Prediction in Bayesian Deep Learning ICLR 2025 Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs JMLR 2025 Post-Processing Temporal Action Detection CVPR 2023 The Shrinkage-Delinkage Trade-off: an Analysis of Factorized Gaussian Approximations for Variational Inference UAI 2023 Strong Gaussian Approximation for the Sum of Random Vectors COLT 2022 Variational inference via Wasserstein gradient flows NeurIPS 2022 Simultaneously Optimizing Weight and Quantizer of Ternary Neural Network Using Truncated Gaussian Approximation CVPR 2019 Density Evolution in the Degree-correlated Stochastic Block Model COLT 2016 Estimating Maximum Expected Value through Gaussian Approximation ICML 2016 Bounding errors of Expectation-Propagation NeurIPS 2015 Gaussian Approximation of Collective Graphical Models ICML 2014 Fast dropout training ICML 2013 Gaussian Kullback-Leibler Approximate Inference JMLR 2013 Concave Gaussian Variational Approximations for Inference in Large-Scale Bayesian Linear Models AISTATS 2011 Active Sequential Learning with Tactile Feedback AISTATS 2010 A Gaussian Tree Approximation for Integer Least-Squares NeurIPS 2009 Adapting to a Market Shock: Optimal Sequential Market-Making NeurIPS 2008 Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification JMLR 2007