automatic relevance determination

Feature Collapsing for Gaussian Process Variable Ranking AISTATS 2022 Hyperparameter Transfer Learning with Adaptive Complexity AISTATS 2021 Kernel Identification Through Transformers NeurIPS 2021 Scalable Bayesian GPFA with automatic relevance determination and discrete noise models NeurIPS 2021 BayesNAS: A Bayesian Approach for Neural Architecture Search ICML 2019 Dependent relevance determination for smooth and structured sparse regression JMLR 2019 Efficient Language Modeling with Automatic Relevance Determination in Recurrent Neural Networks ACL 2019 Identification, Interpretability, and Bayesian Word Embeddings NAACL 2019 Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting IJCAI 2019 Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes NeurIPS 2019 Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution AISTATS 2019 Bayesian Supervised Hashing CVPR 2017 Variational Dropout Sparsifies Deep Neural Networks ICML 2017 Bayesian Adaptive Matrix Factorization With Automatic Model Selection CVPR 2015 Convex vs Non-Convex Estimators for Regression and Sparse Estimation: the Mean Squared Error Properties of ARD and GLasso JMLR 2014 Sparse Bayesian structure learning with “dependent relevance determination” priors NeurIPS 2014 Sparse probabilistic projections NeurIPS 2008 A New View of Automatic Relevance Determination NeurIPS 2007 Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization NeurIPS 2006 Parameter Expanded Variational Bayesian Methods NeurIPS 2006 Sparse Bayesian Learning and the Relevance Vector Machine JMLR 2001