supervised learning

Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence JMLR 2010 Learning To Count Objects in Images NeurIPS 2010 Learning to localise sounds with spiking neural networks NeurIPS 2010 Online Learning: Random Averages, Combinatorial Parameters, and Learnability NeurIPS 2010 On the Theory of Learnining with Privileged Information NeurIPS 2010 Supervised Dimension Reduction Using Bayesian Mixture Modeling AISTATS 2010 Why Does Unsupervised Pre-training Help Deep Learning? AISTATS 2010 Stable and Efficient Gaussian Process Calculations JMLR 2009 Sufficient Conditions for Agnostic Active Learnable NeurIPS 2009 A Library for Locally Weighted Projection Regression JMLR 2008 DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification NeurIPS 2008 Linear Classification and Selective Sampling Under Low Noise Conditions NeurIPS 2008 On the Efficient Minimization of Classification Calibrated Surrogates NeurIPS 2008 Supervised Bipartite Graph Inference NeurIPS 2008 Supervised Dictionary Learning NeurIPS 2008 Unlabeled data: Now it helps, now it doesn't NeurIPS 2008 A general agnostic active learning algorithm NeurIPS 2007 Boosting the Area under the ROC Curve NeurIPS 2007 Hierarchical Penalization NeurIPS 2007 Supervised Topic Models NeurIPS 2007 A Humanlike Predictor of Facial Attractiveness NeurIPS 2006 A Local Learning Approach for Clustering NeurIPS 2006 Estimation of Gradients and Coordinate Covariation in Classification JMLR 2006 Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert Space NeurIPS 2006 Learning Coordinate Covariances via Gradients JMLR 2006