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Bayesian Learning

1663 directly classified papers

Papers per year

Papers

Aggregating and Predicting Sequence Labels from Crowd Annotations ACL 2017
Averaged Collapsed Variational Bayes Inference JMLR 2017
Unified Representation and Lifted Sampling for Generative Models of Social Networks IJCAI 2017
Variational Mixtures of Gaussian Processes for Classification IJCAI 2017
Learning Nonparametric Forest Graphical Models with Prior Information AISTATS 2017
Nonparametric Online Machine Learning with Kernels IJCAI 2017
Bayesian Modeling of Lexical Resources for Low-Resource Settings ACL 2017
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling IJCAI 2017
Comparing Strategic Secrecy and Stackelberg Commitment in Security Games IJCAI 2017
Student-t Process Regression with Student-t Likelihood IJCAI 2017
Discovering Relevance-Dependent Bicluster Structure from Relational Data IJCAI 2017
Discriminative Bayesian Nonparametric Clustering IJCAI 2017
Structured Bayesian Pruning via Log-Normal Multiplicative Noise NIPS 2017
Scalable Model Selection for Belief Networks NIPS 2017
Post-Inference Prior Swapping ICML 2017
Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning IJCAI 2017
Locally Consistent Bayesian Network Scores for Multi-Relational Data IJCAI 2017
Thompson Sampling for Linear-Quadratic Control Problems AISTATS 2017
Strong Syntax Splitting for Iterated Belief Revision IJCAI 2017
Quantifying Aspect Bias in Ordinal Ratings using a Bayesian Approach IJCAI 2017
Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes NIPS 2017
Linearly constrained Gaussian processes NIPS 2017
Bayesian inference on random simple graphs with power law degree distributions ICML 2017
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation ICML 2017
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo ICML 2017