Correction to: On the Convergence of Asynchronous Parallel Iteration with Unbounded Delays
暂无分享,去创建一个
[1] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[2] Yurii Nesterov,et al. Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems , 2012, SIAM J. Optim..
[3] Clifford Hildreth,et al. A quadratic programming procedure , 1957 .
[4] Dimitri P. Bertsekas,et al. Distributed asynchronous computation of fixed points , 1983, Math. Program..
[5] Francisco Facchinei,et al. Asynchronous Parallel Algorithms for Nonconvex Big-Data Optimization: Model and Convergence , 2016, ArXiv.
[6] Andrzej Cichocki,et al. Nonnegative Matrix and Tensor Factorization T , 2007 .
[7] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[8] Damek Davis. The Asynchronous PALM Algorithm for Nonsmooth Nonconvex Problems , 2016, 1604.00526.
[9] Wotao Yin,et al. Augmented 퓁1 and Nuclear-Norm Models with a Globally Linearly Convergent Algorithm , 2012, SIAM J. Imaging Sci..
[10] Aryan Mokhtari,et al. A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning , 2016, J. Mach. Learn. Res..
[11] J. Strikwerda. A probabilistic analysis of asynchronous iteration , 2002 .
[12] R. Tyrrell Rockafellar,et al. Variational Analysis , 1998, Grundlehren der mathematischen Wissenschaften.
[13] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[14] Paul Tseng,et al. A coordinate gradient descent method for nonsmooth separable minimization , 2008, Math. Program..
[15] Wotao Yin,et al. Block Stochastic Gradient Iteration for Convex and Nonconvex Optimization , 2014, SIAM J. Optim..
[16] P. Tseng. Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization , 2001 .
[17] Stephen J. Wright,et al. Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties , 2014, SIAM J. Optim..
[18] Wotao Yin,et al. A Globally Convergent Algorithm for Nonconvex Optimization Based on Block Coordinate Update , 2014, J. Sci. Comput..
[19] Alexander Shapiro,et al. Stochastic Approximation approach to Stochastic Programming , 2013 .
[20] Jack L. Rosenfeld,et al. A case study in programming for parallel-processors , 1969, CACM.
[21] Stephen J. Wright,et al. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent , 2011, NIPS.
[22] Luigi Grippo,et al. On the convergence of the block nonlinear Gauss-Seidel method under convex constraints , 2000, Oper. Res. Lett..
[23] Wotao Yin,et al. On Unbounded Delays in Asynchronous Parallel Fixed-Point Algorithms , 2016, J. Sci. Comput..
[24] Guanghui Lan,et al. Stochastic Block Mirror Descent Methods for Nonsmooth and Stochastic Optimization , 2013, SIAM J. Optim..
[25] Lin Xiao,et al. On the complexity analysis of randomized block-coordinate descent methods , 2013, Mathematical Programming.
[26] A. Gut. Probability: A Graduate Course , 2005 .
[27] R. Tibshirani,et al. Sparse Principal Component Analysis , 2006 .
[28] D. Szyld,et al. On asynchronous iterations , 2000 .
[29] D. Bertsekas,et al. Partially asynchronous, parallel algorithms for network flow and other problems , 1990 .
[30] Peter Richtárik,et al. Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function , 2011, Mathematical Programming.
[31] Ming Yan,et al. ARock: an Algorithmic Framework for Asynchronous Parallel Coordinate Updates , 2015, SIAM J. Sci. Comput..
[32] Stephen J. Wright,et al. An asynchronous parallel stochastic coordinate descent algorithm , 2013, J. Mach. Learn. Res..
[33] Hongtu Zhu,et al. Tensor Regression with Applications in Neuroimaging Data Analysis , 2012, Journal of the American Statistical Association.
[34] Zhi-Quan Luo,et al. Iteration complexity analysis of block coordinate descent methods , 2013, Mathematical Programming.
[35] P. Tseng,et al. On the convergence of the coordinate descent method for convex differentiable minimization , 1992 .
[36] P. Paatero,et al. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values† , 1994 .