classification

Heterogeneous-Neighborhood-based Multi-Task Local Learning Algorithms NeurIPS 2013 Multi-Prediction Deep Boltzmann Machines NeurIPS 2013 Supervised Sequential Classification Under Budget Constraints AISTATS 2013 Local Supervised Learning through Space Partitioning NeurIPS 2012 Beating SGD: Learning SVMs in Sublinear Time NeurIPS 2011 Learning Anchor Planes for Classification NeurIPS 2011 Projection onto A Nonnegative Max-Heap NeurIPS 2011 ShareBoost: Efficient multiclass learning with feature sharing NeurIPS 2011 Agnostic Active Learning Without Constraints NeurIPS 2010 A Reduction from Apprenticeship Learning to Classification NeurIPS 2010 A Theory of Multiclass Boosting NeurIPS 2010 Avoiding False Positive in Multi-Instance Learning NeurIPS 2010 Feature Set Embedding for Incomplete Data NeurIPS 2010 Gated Softmax Classification NeurIPS 2010 Multiple Kernel Learning and the SMO Algorithm NeurIPS 2010 Multitask Learning without Label Correspondences NeurIPS 2010 New Adaptive Algorithms for Online Classification NeurIPS 2010 Regularized Discriminant Analysis, Ridge Regression and Beyond JMLR 2010 Trading off Mistakes and Don't-Know Predictions NeurIPS 2010 Analysis of SVM with Indefinite Kernels NeurIPS 2009 DUOL: A Double Updating Approach for Online Learning NeurIPS 2009 On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost NeurIPS 2008 Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning NeurIPS 2008 Classification via Minimum Incremental Coding Length (MICL) NeurIPS 2007 FilterBoost: Regression and Classification on Large Datasets NeurIPS 2007