Artificial Intelligence

The Generalized FITC Approximation NeurIPS 2007 The Infinite Gamma-Poisson Feature Model NeurIPS 2007 The Infinite Markov Model NeurIPS 2007 The Noisy-Logical Distribution and its Application to Causal Inference NeurIPS 2007 The On-Line Shortest Path Problem Under Partial Monitoring JMLR 2007 Theoretical Analysis of Heuristic Search Methods for Online POMDPs NeurIPS 2007 Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity NeurIPS 2007 The Price of Bandit Information for Online Optimization NeurIPS 2007 The rat as particle filter NeurIPS 2007 The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty RSS 2007 The Value of Labeled and Unlabeled Examples when the Model is Imperfect NeurIPS 2007 Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations NeurIPS 2007 Transfer Learning via Inter-Task Mappings for Temporal Difference Learning JMLR 2007 TrueSkill Through Time: Revisiting the History of Chess NeurIPS 2007 Truncating the Loop Series Expansion for Belief Propagation JMLR 2007 Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NeurIPS 2007 Variational Inference for Diffusion Processes NeurIPS 2007 Variational inference for Markov jump processes NeurIPS 2007 Vision-Aided Inertial Navigation for Precise Planetary Landing: Analysis and Experiments RSS 2007 What makes some POMDP problems easy to approximate? NeurIPS 2007 A Bayesian Approach to Diffusion Models of Decision-Making and Response Time NeurIPS 2006 Accelerated Variational Dirichlet Process Mixtures NeurIPS 2006 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation NeurIPS 2006 Active learning for misspecified generalized linear models NeurIPS 2006 Adaptive Spatial Filters with predefined Region of Interest for EEG based Brain-Computer-Interfaces NeurIPS 2006