Classification

Consistency and Convergence Rates of One-Class SVMs and Related Algorithms JMLR 2006 Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss JMLR 2006 Context Effects in Category Learning: An Investigation of Four Probabilistic Models NeurIPS 2006 Correcting Sample Selection Bias by Unlabeled Data NeurIPS 2006 Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods NeurIPS 2006 Dirichlet-Enhanced Spam Filtering based on Biased Samples NeurIPS 2006 Efficient Learning of Label Ranking by Soft Projections onto Polyhedra JMLR 2006 Enhancing Supervised Terrain Classification with Predictive Unsupervised Learning RSS 2006 Ensemble Pruning Via Semi-definite Programming JMLR 2006 Environment Identification for a Running Robot Using Inertial and Actuator Cues RSS 2006 Estimation of Gradients and Coordinate Covariation in Classification JMLR 2006 Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization JMLR 2006 Fast Discriminative Visual Codebooks using Randomized Clustering Forests NeurIPS 2006 Gait Regulation and Feedback on a Robotic Climbing Hexapod RSS 2006 Generalized Bradley-Terry Models and Multi-Class Probability Estimates JMLR 2006 Geometric entropy minimization (GEM) for anomaly detection and localization NeurIPS 2006 High-Dimensional Graphical Model Selection Using ℓ_1-Regularized Logistic Regression NeurIPS 2006 Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NeurIPS 2006 Incremental Algorithms for Hierarchical Classification JMLR 2006 Incremental Support Vector Learning: Analysis, Implementation and Applications JMLR 2006 In-Network PCA and Anomaly Detection NeurIPS 2006 Isotonic Conditional Random Fields and Local Sentiment Flow NeurIPS 2006 Kernel-Based Learning of Hierarchical Multilabel Classification Models JMLR 2006 Large Margin Component Analysis NeurIPS 2006 Large Margin Hidden Markov Models for Automatic Speech Recognition NeurIPS 2006