Classification

Margin-based Ranking and an Equivalence between AdaBoost and RankBoost JMLR 2009 Maximum Entropy Discrimination Markov Networks JMLR 2009 Modeling the spacing effect in sequential category learning NeurIPS 2009 Model Monitor (M2): Evaluating, Comparing, and Monitoring Models JMLR 2009 Multi-Label Prediction via Compressed Sensing NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA NeurIPS 2009 Multiple Incremental Decremental Learning of Support Vector Machines NeurIPS 2009 NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM JMLR 2009 Nieme: Large-Scale Energy-Based Models JMLR 2009 Noisy Generalized Binary Search NeurIPS 2009 Nonextensive Information Theoretic Kernels on Measures JMLR 2009 Nonlinear Models Using Dirichlet Process Mixtures JMLR 2009 Non-parametric learning to aid path planning over slopes RSS 2009 On Efficient Large Margin Semisupervised Learning: Method and Theory JMLR 2009 On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation NeurIPS 2009 On the Consistency of Feature Selection using Greedy Least Squares Regression JMLR 2009 Optimal Scoring for Unsupervised Learning NeurIPS 2009 Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization JMLR 2009 Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification NeurIPS 2009 Particle Swarm Model Selection JMLR 2009 Positive Semidefinite Metric Learning with Boosting NeurIPS 2009 Potential-Based Agnostic Boosting NeurIPS 2009 Ranking Measures and Loss Functions in Learning to Rank NeurIPS 2009 Regularized Distance Metric Learning:Theory and Algorithm NeurIPS 2009 Robustness and Regularization of Support Vector Machines JMLR 2009