large-scale learning

Distributed training of Large-scale Logistic models ICML 2013 GURLS: A Least Squares Library for Supervised Learning JMLR 2013 Large-Scale Learning with Less RAM via Randomization ICML 2013 Quantile Regression for Large-scale Applications ICML 2013 Translating Embeddings for Modeling Multi-relational Data NeurIPS 2013 Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training JMLR 2012 One Permutation Hashing NeurIPS 2012 Hashing Algorithms for Large-Scale Learning NeurIPS 2011 Large-Scale Category Structure Aware Image Categorization NeurIPS 2011 Erratum: SGDQN is Less Careful than Expected JMLR 2010 The SHOGUN Machine Learning Toolbox JMLR 2010 Factor Modeling for Advertisement Targeting NeurIPS 2009 Nieme: Large-Scale Energy-Based Models JMLR 2009 SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent JMLR 2009 From Online to Batch Learning with Cutoff-Averaging NeurIPS 2008 LIBLINEAR: A Library for Large Linear Classification JMLR 2008 A Randomized Algorithm for Large Scale Support Vector Learning NeurIPS 2007 Comments on the “Core Vector Machines: Fast SVM Training on Very Large Data Sets" JMLR 2007 FilterBoost: Regression and Classification on Large Datasets NeurIPS 2007 Random Features for Large-Scale Kernel Machines NeurIPS 2007 The Tradeoffs of Large Scale Learning NeurIPS 2007 A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs JMLR 2005 SVMTorch: Support Vector Machines for Large-Scale Regression Problems JMLR 2001