model selection

An Asymptotic Behaviour of the Marginal Likelihood for General Markov Models JMLR 2011 Approximate Model Selection for Large Scale LSSVM ACML 2011 Bagged Structure Learning of Bayesian Network AISTATS 2011 Cross-Domain Object Matching with Model Selection AISTATS 2011 Greedy Model Averaging NeurIPS 2011 Hyper-Sparse Optimal Aggregation JMLR 2011 -Norm Multiple Kernel Learning JMLR 2011 On U-processes and clustering performance NeurIPS 2011 Oracle inequalities for computationally budgeted model selection COLT 2011 Selecting the State-Representation in Reinforcement Learning NeurIPS 2011 Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC NeurIPS 2011 The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers NeurIPS 2011 A generalization of the Multiple-try Metropolis algorithm for Bayesian estimation and model selection AISTATS 2010 Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory JMLR 2010 Bayesian Generalized Kernel Models AISTATS 2010 Discriminative Clustering by Regularized Information Maximization NeurIPS 2010 Extended Bayesian Information Criteria for Gaussian Graphical Models NeurIPS 2010 Fast and Scalable Local Kernel Machines JMLR 2010 Model Selection: Beyond the Bayesian/Frequentist Divide JMLR 2010 On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation JMLR 2010 PAC-Bayesian Model Selection for Reinforcement Learning NeurIPS 2010 Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NeurIPS 2010 The LASSO risk: asymptotic results and real world examples NeurIPS 2010 Adaptive Design Optimization in Experiments with People NeurIPS 2009 Data-driven calibration of linear estimators with minimal penalties NeurIPS 2009