Artificial Intelligence

Learning GP-BayesFilters via Gaussian process latent variable models RSS 2009 Learning in Markov Random Fields using Tempered Transitions NeurIPS 2009 Learning Linear Ranking Functions for Beam Search with Application to Planning JMLR 2009 Learning models of object structure NeurIPS 2009 Learning of 2D grasping strategies from box-based 3D object approximations RSS 2009 Learning to Explore and Exploit in POMDPs NeurIPS 2009 Learning with Compressible Priors NeurIPS 2009 Linearly constrained Bayesian matrix factorization for blind source separation NeurIPS 2009 Localizing Bugs in Program Executions with Graphical Models NeurIPS 2009 Local Rules for Global MAP: When Do They Work ? NeurIPS 2009 LQR-trees: Feedback motion planning on sparse randomized trees RSS 2009 Manifold Regularization for SIR with Rate Root-n Convergence NeurIPS 2009 Marginal Likelihood Integrals for Mixtures of Independence Models JMLR 2009 Markov Properties for Linear Causal Models with Correlated Errors JMLR 2009 Maximum Entropy Discrimination Markov Networks JMLR 2009 Measuring model complexity with the prior predictive NeurIPS 2009 Modeling the spacing effect in sequential category learning NeurIPS 2009 Modelling Relational Data using Bayesian Clustered Tensor Factorization NeurIPS 2009 Monte Carlo Sampling for Regret Minimization in Extensive Games NeurIPS 2009 Multi-Step Dyna Planning for Policy Evaluation and Control NeurIPS 2009 Nash Equilibria of Static Prediction Games NeurIPS 2009 Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling NeurIPS 2009 Noisy Generalized Binary Search NeurIPS 2009 Nonlinear directed acyclic structure learning with weakly additive noise models NeurIPS 2009 Nonlinear Learning using Local Coordinate Coding NeurIPS 2009