Classification

Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models NeurIPS 2010 Variable margin losses for classifier design NeurIPS 2010 AUC optimization and the two-sample problem NeurIPS 2009 Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition NeurIPS 2009 Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification NeurIPS 2009 Zero-shot Learning with Semantic Output Codes NeurIPS 2009 Adaptive Martingale Boosting NeurIPS 2008 DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification NeurIPS 2008 On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost NeurIPS 2008 Privacy-preserving logistic regression NeurIPS 2008 Supervised Dictionary Learning NeurIPS 2008 A Risk Minimization Principle for a Class of Parzen Estimators NeurIPS 2007 Boosting the Area under the ROC Curve NeurIPS 2007 Discriminative Batch Mode Active Learning NeurIPS 2007 FilterBoost: Regression and Classification on Large Datasets NeurIPS 2007 Learning Monotonic Transformations for Classification NeurIPS 2007 Multiple-Instance Pruning For Learning Efficient Cascade Detectors NeurIPS 2007 The Generalized FITC Approximation NeurIPS 2007 Fast Discriminative Visual Codebooks using Randomized Clustering Forests NeurIPS 2006 Large Margin Hidden Markov Models for Automatic Speech Recognition NeurIPS 2006 Ordinal Regression by Extended Binary Classification NeurIPS 2006