L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework

Reference EPFL-REPORT-229241 URL: http://arxiv.org/abs/1512.04011 Record created on 2017-06-21, modified on 2017-07-12

[1]  S. Kakade,et al.  On the duality of strong convexity and strong smoothness : Learning applications and matrix regularization , 2009 .

[2]  Ameet Talwalkar,et al.  MLlib: Machine Learning in Apache Spark , 2015, J. Mach. Learn. Res..

[3]  Ilya Trofimov,et al.  Distributed Coordinate Descent for L1-regularized Logistic Regression , 2015, AIST.

[4]  S. V. N. Vishwanathan,et al.  A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning , 2008, J. Mach. Learn. Res..

[5]  丸山 徹.  Convex Analysisの二,三の進展について , 1977 .

[6]  Tyler B. Johnson,et al.  Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization , 2015, ICML.

[7]  Shai Shalev-Shwartz,et al.  Stochastic dual coordinate ascent methods for regularized loss , 2012, J. Mach. Learn. Res..

[8]  Shou-De Lin,et al.  A Dual Augmented Block Minimization Framework for Learning with Limited Memory , 2015, NIPS.

[9]  Virginia Smith,et al.  Distributed Optimization for Non-Strongly Convex Regularizers , 2016 .

[10]  Ambuj Tewari,et al.  Stochastic methods for l1 regularized loss minimization , 2009, ICML '09.

[11]  Chih-Jen Lin,et al.  A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification , 2010, J. Mach. Learn. Res..

[12]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[13]  Lin Xiao,et al.  On the complexity analysis of randomized block-coordinate descent methods , 2013, Mathematical Programming.

[14]  Peter Richtárik,et al.  SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization , 2015, ICML.

[15]  Dongyeop Kang,et al.  Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression , 2014, CIKM.

[16]  Tong Zhang,et al.  Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization , 2013, Math. Program..

[17]  Tianbao Yang,et al.  Trading Computation for Communication: Distributed Stochastic Dual Coordinate Ascent , 2013, NIPS.

[18]  S. Sundararajan,et al.  A distributed block coordinate descent method for training $l_1$ regularized linear classifiers , 2014, J. Mach. Learn. Res..

[19]  Martin Jaggi,et al.  An Equivalence between the Lasso and Support Vector Machines , 2013, ArXiv.

[20]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[21]  Jianfeng Gao,et al.  Scalable training of L1-regularized log-linear models , 2007, ICML '07.

[22]  Chia-Hua Ho,et al.  An improved GLMNET for l1-regularized logistic regression , 2011, J. Mach. Learn. Res..

[23]  Ion Necoara,et al.  Parallel Random Coordinate Descent Method for Composite Minimization: Convergence Analysis and Error Bounds , 2016, SIAM J. Optim..

[24]  Yuchen Zhang,et al.  Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization , 2014, ICML.

[25]  Martin Jaggi,et al.  Primal-Dual Rates and Certificates , 2016, ICML.

[26]  Yurii Nesterov,et al.  Smooth minimization of non-smooth functions , 2005, Math. Program..

[27]  Stephen P. Boyd,et al.  Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..

[28]  Heinz H. Bauschke,et al.  Convex Analysis and Monotone Operator Theory in Hilbert Spaces , 2011, CMS Books in Mathematics.

[29]  Joseph K. Bradley,et al.  Parallel Coordinate Descent for L1-Regularized Loss Minimization , 2011, ICML.

[30]  Michael I. Jordan,et al.  Adding vs. Averaging in Distributed Primal-Dual Optimization , 2015, ICML.

[31]  Tong Zhang,et al.  A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization , 2016, J. Mach. Learn. Res..

[32]  Martin Wattenberg,et al.  Ad click prediction: a view from the trenches , 2013, KDD.

[33]  Simone Forte.  Distributed Optimization for Non-Strongly Convex Regularizers , 2015 .

[34]  Thomas Hofmann,et al.  Communication-Efficient Distributed Dual Coordinate Ascent , 2014, NIPS.

[35]  Peter Richtárik,et al.  Accelerated, Parallel, and Proximal Coordinate Descent , 2013, SIAM J. Optim..