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Michael I. Jordan | Martin Jaggi | Peter Richtárik | Martin Takác | Chenxin Ma | Virginia Smith | Martin Jaggi | Peter Richtárik | Virginia Smith | Chenxin Ma | Martin Takác
[1] Gideon S. Mann,et al. Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models , 2009, NIPS.
[2] Alexander J. Smola,et al. Parallelized Stochastic Gradient Descent , 2010, NIPS.
[3] Georgios B. Giannakis,et al. Consensus-Based Distributed Support Vector Machines , 2010, J. Mach. Learn. Res..
[4] Stephen J. Wright,et al. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent , 2011, NIPS.
[5] Dmitry Pechyony,et al. Solving Large Scale Linear SVM with Distributed Block Minimization , 2011 .
[6] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[7] Martin J. Wainwright,et al. Communication-efficient algorithms for statistical optimization , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).
[8] Maria-Florina Balcan,et al. Distributed Learning, Communication Complexity and Privacy , 2012, COLT.
[9] Michael J. Franklin,et al. Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing , 2012, NSDI.
[10] Chih-Jen Lin,et al. Large Linear Classification When Data Cannot Fit in Memory , 2011, TKDD.
[11] Rong Jin,et al. On Theoretical Analysis of Distributed Stochastic Dual Coordinate Ascent , 2013, ArXiv.
[12] Shai Shalev-Shwartz,et al. Stochastic dual coordinate ascent methods for regularized loss , 2012, J. Mach. Learn. Res..
[13] Shai Shalev-Shwartz,et al. Accelerated Mini-Batch Stochastic Dual Coordinate Ascent , 2013, NIPS.
[14] Rong Jin,et al. Analysis of Distributed Stochastic Dual Coordinate Ascent , 2013, 1312.1031.
[15] Michael I. Jordan,et al. Estimation, Optimization, and Parallelism when Data is Sparse , 2013, NIPS.
[16] Tianbao Yang,et al. Trading Computation for Communication: Distributed Stochastic Dual Coordinate Ascent , 2013, NIPS.
[17] Thomas Hofmann,et al. Communication-Efficient Distributed Dual Coordinate Ascent , 2014, NIPS.
[18] Peter Richtárik,et al. Fast distributed coordinate descent for non-strongly convex losses , 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).
[19] Ohad Shamir,et al. Communication-Efficient Distributed Optimization using an Approximate Newton-type Method , 2013, ICML.
[20] Ohad Shamir,et al. Distributed stochastic optimization and learning , 2014, 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton).
[21] Peter Richtárik,et al. Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function , 2011, Mathematical Programming.
[22] Brian McWilliams,et al. LOCO: Distributing Ridge Regression with Random Projections , 2014, 1406.3469.
[23] Peter Richtárik,et al. Randomized Dual Coordinate Ascent with Arbitrary Sampling , 2014, ArXiv.
[24] Lin Xiao,et al. On the complexity analysis of randomized block-coordinate descent methods , 2013, Mathematical Programming.
[25] Stephen J. Wright,et al. An asynchronous parallel stochastic coordinate descent algorithm , 2013, J. Mach. Learn. Res..
[26] Peter Richtárik,et al. Distributed Block Coordinate Descent for Minimizing Partially Separable Functions , 2014, 1406.0238.
[27] Yuchen Zhang,et al. Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss , 2015, ArXiv.
[28] Peter Richtárik,et al. Accelerated, Parallel, and Proximal Coordinate Descent , 2013, SIAM J. Optim..
[29] Dan Roth,et al. Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM , 2015, ICML.
[30] Stephen J. Wright,et al. Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties , 2014, SIAM J. Optim..
[31] Yuchen Zhang,et al. DiSCO: Distributed Optimization for Self-Concordant Empirical Loss , 2015, ICML.
[32] Peter Richtárik,et al. Coordinate descent with arbitrary sampling I: algorithms and complexity† , 2014, Optim. Methods Softw..
[33] Peter Richtárik,et al. Distributed Coordinate Descent Method for Learning with Big Data , 2013, J. Mach. Learn. Res..
[34] Tong Zhang,et al. Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization , 2013, Math. Program..
[35] Peter Richtárik,et al. On optimal probabilities in stochastic coordinate descent methods , 2013, Optim. Lett..
[36] Peter Richtárik,et al. Parallel coordinate descent methods for big data optimization , 2012, Mathematical Programming.
[37] Michael I. Jordan,et al. Distributed optimization with arbitrary local solvers , 2015, Optim. Methods Softw..