Bayesian Learning

Agreement-Based Learning NeurIPS 2007 A neural network implementing optimal state estimation based on dynamic spike train decoding NeurIPS 2007 A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning JMLR 2007 A New View of Automatic Relevance Determination NeurIPS 2007 Bayes-Adaptive POMDPs NeurIPS 2007 Bayesian Agglomerative Clustering with Coalescents NeurIPS 2007 Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms NeurIPS 2007 Bayesian Co-Training NeurIPS 2007 Bayesian Inference for Spiking Neuron Models with a Sparsity Prior NeurIPS 2007 Bayesian Policy Learning with Trans-Dimensional MCMC NeurIPS 2007 Building Blocks for Variational Bayesian Learning of Latent Variable Models JMLR 2007 Catching Up Faster in Bayesian Model Selection and Model Averaging NeurIPS 2007 Characterizing the Function Space for Bayesian Kernel Models JMLR 2007 Collapsed Variational Inference for HDP NeurIPS 2007 Comparing Bayesian models for multisensory cue combination without mandatory integration NeurIPS 2007 Distributed Inference for Latent Dirichlet Allocation NeurIPS 2007 Efficient Bayesian Inference for Dynamically Changing Graphs NeurIPS 2007 Fast Variational Inference for Large-scale Internet Diagnosis NeurIPS 2007 Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders RSS 2007 Hidden Common Cause Relations in Relational Learning NeurIPS 2007 "Ideal Parent” Structure Learning for Continuous Variable Bayesian Networks JMLR 2007 Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes NeurIPS 2007 Infinite State Bayes-Nets for Structured Domains NeurIPS 2007 Markov Chain Monte Carlo with People NeurIPS 2007 Multi-task Gaussian Process Prediction NeurIPS 2007