binary classification

Active Comparison of Prediction Models NeurIPS 2012 Learning as MAP Inference in Discrete Graphical Models NeurIPS 2012 Multiclass Learning Approaches: A Theoretical Comparison with Implications NeurIPS 2012 Open Problem: Better Bounds for Online Logistic Regression COLT 2012 Probabilistic n-Choose-k Models for Classification and Ranking NeurIPS 2012 Reducing statistical time-series problems to binary classification NeurIPS 2012 Volume Regularization for Binary Classification NeurIPS 2012 An Exact Algorithm for F-Measure Maximization NeurIPS 2011 Hashing Algorithms for Large-Scale Learning NeurIPS 2011 Information, Divergence and Risk for Binary Experiments JMLR 2011 Neyman-Pearson Classification, Convexity and Stochastic Constraints JMLR 2011 Neyman-Pearson classification under a strict constraint COLT 2011 A Theory of Multiclass Boosting NeurIPS 2010 Avoiding False Positive in Multi-Instance Learning NeurIPS 2010 Classification Methods with Reject Option Based on Convex Risk Minimization JMLR 2010 Composite Binary Losses JMLR 2010 Convexity of Proper Composite Binary Losses AISTATS 2010 Convex Multiple-Instance Learning by Estimating Likelihood Ratio NeurIPS 2010 Learning Translation Invariant Kernels for Classification JMLR 2010 Online Classification with Specificity Constraints NeurIPS 2010 Rademacher Complexities and Bounding the Excess Risk in Active Learning JMLR 2010 Semi-Supervised Novelty Detection JMLR 2010 The Coding Divergence for Measuring the Complexity of Separating Two Sets ACML 2010 Universal Consistency of Multi-Class Support Vector Classification NeurIPS 2010 Adaptive Regularization of Weight Vectors NeurIPS 2009