Adaptive Sampling Probabilities for Non-Smooth Optimization
暂无分享,去创建一个
John C. Duchi | Hongseok Namkoong | Aman Sinha | Steve Yadlowsky | Hongseok Namkoong | S. Yadlowsky | Aman Sinha | Steve Yadlowsky
[1] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Siddharth Gopal,et al. Adaptive Sampling for SGD by Exploiting Side Information , 2016, ICML.
[3] Marc Teboulle,et al. Mirror descent and nonlinear projected subgradient methods for convex optimization , 2003, Oper. Res. Lett..
[4] Shai Shalev-Shwartz,et al. Online Learning and Online Convex Optimization , 2012, Found. Trends Mach. Learn..
[5] Tong Zhang,et al. Accelerating Minibatch Stochastic Gradient Descent using Stratified Sampling , 2014, ArXiv.
[6] Yurii Nesterov,et al. Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems , 2012, SIAM J. Optim..
[7] Arnold W. M. Smeulders,et al. The Amsterdam Library of Object Images , 2004, International Journal of Computer Vision.
[8] Matthew J. Streeter,et al. Adaptive Bound Optimization for Online Convex Optimization , 2010, COLT 2010.
[9] Zeyuan Allen Zhu,et al. Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling , 2015, ICML.
[10] R. Vershynin,et al. A Randomized Kaczmarz Algorithm with Exponential Convergence , 2007, math/0702226.
[11] Alexander Shapiro,et al. Stochastic Approximation approach to Stochastic Programming , 2013 .
[12] Gábor Lugosi,et al. Prediction, learning, and games , 2006 .
[13] Yin Tat Lee,et al. Efficient Accelerated Coordinate Descent Methods and Faster Algorithms for Solving Linear Systems , 2013, 2013 IEEE 54th Annual Symposium on Foundations of Computer Science.
[14] Guanghui Lan,et al. Stochastic Block Mirror Descent Methods for Nonsmooth and Stochastic Optimization , 2013, SIAM J. Optim..
[15] Lin Xiao,et al. On the complexity analysis of randomized block-coordinate descent methods , 2013, Mathematical Programming.
[16] Tong Zhang,et al. Proximal Stochastic Dual Coordinate Ascent , 2012, ArXiv.
[17] Tong Zhang,et al. Stochastic Optimization with Importance Sampling , 2014, ArXiv.
[18] Mark W. Schmidt,et al. Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection , 2015, ICML.
[19] Amir Beck,et al. On the Convergence of Block Coordinate Descent Type Methods , 2013, SIAM J. Optim..
[20] Peter Richtárik,et al. Stochastic Dual Coordinate Ascent with Adaptive Probabilities , 2015, ICML.
[21] Sébastien Bubeck,et al. Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems , 2012, Found. Trends Mach. Learn..
[22] R. Stewart,et al. Quantitative selection and parallel characterization of aptamers , 2013, Proceedings of the National Academy of Sciences.
[23] Christopher Ré,et al. Weighted SGD for ℓp Regression with Randomized Preconditioning , 2015, SODA.
[24] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[25] Pietro Perona,et al. The Caltech-UCSD Birds-200-2011 Dataset , 2011 .
[26] Peter Richtárik,et al. Importance Sampling for Minibatches , 2016, J. Mach. Learn. Res..
[27] Peter Richtárik,et al. Parallel coordinate descent methods for big data optimization , 2012, Mathematical Programming.
[28] Y. Nesterov,et al. A RANDOM COORDINATE DESCENT METHOD ON LARGE-SCALE OPTIMIZATION PROBLEMS WITH LINEAR CONSTRAINTS , 2013 .
[29] Tong Zhang,et al. Stochastic Optimization with Importance Sampling for Regularized Loss Minimization , 2014, ICML.
[30] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[31] Tong Zhang,et al. Accelerating Stochastic Gradient Descent using Predictive Variance Reduction , 2013, NIPS.
[32] Peter Richtárik,et al. Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function , 2011, Mathematical Programming.
[33] Deanna Needell,et al. Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm , 2013, Mathematical Programming.
[34] Francis Bach,et al. SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives , 2014, NIPS.
[35] John Darzentas,et al. Problem Complexity and Method Efficiency in Optimization , 1983 .