Artificial Intelligence

Lifted Inference Seen from the Other Side : The Tractable Features NeurIPS 2010 Linear readout from a neural population with partial correlation data NeurIPS 2010 Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation JMLR 2010 Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions JMLR 2010 LQG-MP: Optimized Path Planning for Robots with Motion Uncertainty and Imperfect State Information RSS 2010 LSTD with Random Projections NeurIPS 2010 MAP Estimation for Graphical Models by Likelihood Maximization NeurIPS 2010 Matrix-Variate Dirichlet Process Mixture Models AISTATS 2010 Maximum-likelihood learning of cumulative distribution functions on graphs AISTATS 2010 Mixture of time-warped trajectory models for movement decoding NeurIPS 2010 Modeling annotator expertise: Learning when everybody knows a bit of something AISTATS 2010 Monte-Carlo Planning in Large POMDPs NeurIPS 2010 More data means less inference: A pseudo-max approach to structured learning NeurIPS 2010 Movement extraction by detecting dynamics switches and repetitions NeurIPS 2010 Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers NeurIPS 2010 Multitask Learning for Brain-Computer Interfaces AISTATS 2010 Multi-Task Learning using Generalized t Process AISTATS 2010 Multitask Learning without Label Correspondences NeurIPS 2010 Multi-View Active Learning in the Non-Realizable Case NeurIPS 2010 Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks NeurIPS 2010 Near-Optimal Bayesian Active Learning with Noisy Observations NeurIPS 2010 Near-Optimal Evasion of Convex-Inducing Classifiers AISTATS 2010 Neural conditional random fields AISTATS 2010 Nonparametric Bayesian Matrix Factorization by Power-EP AISTATS 2010 Nonparametric Bayesian Policy Priors for Reinforcement Learning NeurIPS 2010