logistic regression

Linear-Time Estimators for Propensity Scores AISTATS 2011 Non-conjugate Variational Message Passing for Multinomial and Binary Regression NeurIPS 2011 On Learning Discrete Graphical Models using Group-Sparse Regularization AISTATS 2011 Statistical Tests for Optimization Efficiency NeurIPS 2011 Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation JMLR 2011 Unsupervised Supervised Learning II: Margin-Based Classification without Labels AISTATS 2011 A Fast Hybrid Algorithm for Large-Scale -Regularized Logistic Regression JMLR 2010 An Investigation of Missing Data Methods for Classification Trees Applied to Binary Response Data JMLR 2010 Boosted Optimization for Network Classification AISTATS 2010 Bundle Methods for Regularized Risk Minimization JMLR 2010 Noise-contrastive estimation: A new estimation principle for unnormalized statistical models AISTATS 2010 Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification NeurIPS 2010 t-logistic regression NeurIPS 2010 Heterogeneous multitask learning with joint sparsity constraints NeurIPS 2009 Learning Nondeterministic Classifiers JMLR 2009 A Multiple Instance Learning Strategy for Combating Good Word Attacks on Spam Filters JMLR 2008 Evidence Contrary to the Statistical View of Boosting JMLR 2008 Generative versus discriminative training of RBMs for classification of fMRI images NeurIPS 2008 LIBLINEAR: A Library for Large Linear Classification JMLR 2008 Privacy-preserving logistic regression NeurIPS 2008 Reconciling Real Scores with Binary Comparisons: A New Logistic Based Model for Ranking NeurIPS 2008 Trust Region Newton Method for Logistic Regression JMLR 2008 An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression JMLR 2007 FilterBoost: Regression and Classification on Large Datasets NeurIPS 2007 Infinitely Imbalanced Logistic Regression JMLR 2007