The effect of deterministic noise in subgradient methods
暂无分享,去创建一个
[1] E. A. Nurminskii. Minimization of nondifferentiable functions in the presence of noise , 1974 .
[2] Yuri Ermoliev,et al. Stochastic Programming Methods , 1976 .
[3] B. T. Poljak. Nonlinear programming methods in the presence of noise , 1978, Math. Program..
[4] Y. Ermoliev. Stochastic quasigradient methods and their application to system optimization , 1983 .
[5] Yuri Ermoliev,et al. Numerical techniques for stochastic optimization , 1988 .
[6] Yuri Ermoliev,et al. Stochastic quasigradient methods. Numerical techniques for stochastic optimization , 1988 .
[7] M. Ferris,et al. Weak sharp minima in mathematical programming , 1993 .
[8] Dimitri P. Bertsekas,et al. Nonlinear Programming , 1995 .
[9] O. Nelles,et al. An Introduction to Optimization , 1996, IEEE Antennas and Propagation Magazine.
[10] Y. Censor,et al. Inherently parallel algorithms in feasibility and applications , 1997 .
[11] Jong-Shi Pang,et al. Error bounds in mathematical programming , 1997, Math. Program..
[12] M. Solodov,et al. Error Stability Properties of Generalized Gradient-Type Algorithms , 1998 .
[13] Jean-Louis Goffin,et al. Convergence of a simple subgradient level method , 1999, Math. Program..
[14] D. Bertsekas,et al. Incremental subgradient methods for nondifferentiable optimization , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).
[15] Vivek S. Borkar,et al. Distributed Asynchronous Incremental Subgradient Methods , 2001 .
[16] D. Bertsekas,et al. Convergen e Rate of In remental Subgradient Algorithms , 2000 .
[17] Arkadi Nemirovski,et al. The Ordered Subsets Mirror Descent Optimization Method with Applications to Tomography , 2001, SIAM J. Optim..
[18] S. Uryasev,et al. Stochastic optimization : Algorithms and Applications , 2001 .
[19] Angelia Nedic,et al. Subgradient methods for convex minimization , 2002 .
[20] Dimitri P. Bertsekas,et al. Convex Analysis and Optimization , 2003 .
[21] Krzysztof C. Kiwiel,et al. Convergence of Approximate and Incremental Subgradient Methods for Convex Optimization , 2003, SIAM J. Optim..
[22] Robert D. Nowak,et al. Quantized incremental algorithms for distributed optimization , 2005, IEEE Journal on Selected Areas in Communications.
[23] Krzysztof C. Kiwiel,et al. A Proximal Bundle Method with Approximate Subgradient Linearizations , 2006, SIAM J. Optim..
[24] Giovanna Miglionico,et al. An Incremental Method for Solving Convex Finite Min-Max Problems , 2006, Math. Oper. Res..
[25] R. Srikant,et al. Quantized Consensus , 2006, 2006 IEEE International Symposium on Information Theory.
[26] T. C. Aysal,et al. Distributed Average Consensus With Dithered Quantization , 2008, IEEE Transactions on Signal Processing.
[27] Samir Elhedhli,et al. Nondifferentiable Optimization , 2009, Encyclopedia of Optimization.
[28] Yuri M. Ermoliev. Stochastic Quasigradient Methods , 2009, Encyclopedia of Optimization.