Convergence of Approximate and Incremental Subgradient Methods for Convex Optimization
暂无分享,去创建一个
[1] K. Schulz. A note on the convergence of subgradient optimization methods , 1983 .
[2] Zhi-Quan Luo,et al. On the Convergence of the LMS Algorithm with Adaptive Learning Rate for Linear Feedforward Networks , 1991, Neural Computation.
[3] J. Hiriart-Urruty,et al. Convex analysis and minimization algorithms , 1993 .
[4] Claude Lemaréchal,et al. Convergence of some algorithms for convex minimization , 1993, Math. Program..
[5] A. Shapiro,et al. Convergence analysis of gradient descent stochastic algorithms , 1996 .
[6] O. Nelles,et al. An Introduction to Optimization , 1996, IEEE Antennas and Propagation Magazine.
[7] M. Patriksson,et al. Conditional subgradient optimization -- Theory and applications , 1996 .
[8] Dimitri P. Bertsekas,et al. A New Class of Incremental Gradient Methods for Least Squares Problems , 1997, SIAM J. Optim..
[9] Alfredo N. Iusem,et al. On the projected subgradient method for nonsmooth convex optimization in a Hilbert space , 1998, Math. Program..
[10] Jean-Louis Goffin,et al. Convergence of a simple subgradient level method , 1999, Math. Program..
[11] John N. Tsitsiklis,et al. Gradient Convergence in Gradient methods with Errors , 1999, SIAM J. Optim..
[12] Arkadi Nemirovski,et al. The Ordered Subsets Mirror Descent Optimization Method with Applications to Tomography , 2001, SIAM J. Optim..