Fetching the paper…
Reading the bibliography…
Despite the importance of sparsity in many large-scale applications, there are few methods for distributed optimization of sparsity-inducing objectives.
Convex Analysis
R. T. Rockafellar · 1997
Earlier work this paper cites.
Convex Optimization
S. Boyd and L. Vandenberghe · 2004
Earlier work this paper cites.
Techniques of Variational Analysis and Nonlinear Optimization
J. M. Borwein and Q. Zhu · 2005
Earlier work this paper cites.
Smooth minimization of non-smooth functions
Y. Nesterov · 2005
Earlier work this paper cites.
Scalable training of L1-regularized log-linear models
G. Andrew and J. Gao · 2007
Earlier work this paper cites.
On the duality of strong convexity and strong smoothness: Learning applications and matrix regularization
S. M. Kakade, S. Shalev-Shwartz, and A. Tewari · 2009
Earlier work this paper cites.
Distributed optimization and statistical learning via the alternating direction method of multipliers
S. Boyd et al · 2010
Earlier work this paper cites.
Regularization paths for generalized linear models via coordinate descent
J. Friedman, T. Hastie, and R. Tibshirani · 2010
Earlier work this paper cites.
A quasi-newton approach to nonsmooth convex optimization problems in machine learning
J. Yu, S. Vishwanathan, S. Günter, and N. N. Schraudolph · 2010
Earlier work this paper cites.
A comparison of optimization methods and software for large-scale l1-regularized linear classification
G.-X. Yuan et al · 2010
Earlier work this paper cites.
Convex Analysis and Monotone Operator Theory in Hilbert Spaces
H. H. Bauschke and P. L. Combettes · 2011
Earlier work this paper cites.
Parallel coordinate descent for l1-regularized loss minimization
J. K. Bradley et al · 2011
Earlier work this paper cites.
Stochastic methods for l 1
S. Shalev-Shwartz and A. Tewari · 2011
Cited alongside, same era.
An improved glmnet for l1-regularized logistic regression
G.-X. Yuan, C.-H. Ho, and C.-J. Lin · 2012
Cited alongside, same era.
Parallel coordinate descent newton method for efficient g g 1
Y. Bian et al · 2013
Cited alongside, same era.
On the complexity analysis of randomized block-coordinate descent methods
Z. Lu and L. Xiao · 2013
Cited alongside, same era.
Ad click prediction: a view from the trenches
H. B. McMahan et al · 2013
Cited alongside, same era.
Stochastic dual coordinate ascent methods for regularized loss minimization
S. Shalev-Shwartz and T. Zhang · 2013
Cited alongside, same era.
Accelerated, Parallel, and Proximal Coordinate Descent
O. Fercoq and P. Richtárik · 2015
Closest in time.
Distributed Optimization for Non-Strongly Convex Regularizers
S. Forte · 2015
Closest in time.
Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization
T. Johnson and C. Guestrin · 2015
Closest in time.
Adding vs. averaging in distributed primal-dual optimization
C. Ma et al · 2015
Closest in time.
Mllib: Machine learning in apache spark
X. Meng et al · 2015
Closest in time.
SDNA: Stochastic dual newton ascent for empirical risk minimization
Z. Qu et al · 2015
Closest in time.
On the complexity of parallel coordinate descent
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Trading computation for communication: Distributed stochastic dual coordinate ascent
T. Yang · 2013
Cited alongside, same era.
Communication-efficient distributed dual coordinate ascent
M. Jaggi et al · 2014
Cited alongside, same era.
Data/feature distributed stochastic coordinate descent for logistic regression
Kang et al · 2014
Cited alongside, same era.
A distributed block coordinate descent method for training l 1 l_{1} regularized linear classifiers
D. Mahajan, S. S. Keerthi, and S. Sundararajan · 2014
Cited alongside, same era.
Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization
S. Shalev-Shwartz and T. Zhang · 2014
Cited alongside, same era.
Distributed coordinate descent for l1-regularized logistic regression
I. Trofimov and A. Genkin · 2014
Cited alongside, same era.
R. Tappenden and P. Richtárik · 2015
Closest in time.
A Dual Augmented Block Minimization Framework for Learning with Limited Memory
I. E.-H. Yen, S.-W. Lin, and S.-D. Lin · 2015
Closest in time.
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
Y. Zhang and X. Lin · 2015
Closest in time.
Primal-Dual Rates and Certificates
C. Dünner et al · 2016
Closest in time.
Parallel Random Coordinate Descent Method for Composite Minimization: Convergence Analysis and Error Bounds
I. Necoara and D. Clipici · 2016
Closest in time.
A general distributed dual coordinate optimization framework for regularized loss minimization
S. Zheng et al · 2016
Closest in time.