On stochastic gradient and subgradient methods with adaptive steplength sequences

[1]  O. Nelles,et al.  An Introduction to Optimization , 1996, IEEE Antennas and Propagation Magazine.

[2]  Peter W. Glynn,et al.  A Complementarity Framework for Forward Contracting Under Uncertainty , 2011, Oper. Res..

[3]  Angelia Nedic,et al.  Single timescale regularized stochastic approximation schemes for monotone Nash games under uncertainty , 2010, 49th IEEE Conference on Decision and Control (CDC).

[4]  Angelia Nedic,et al.  Random projection algorithms for convex set intersection problems , 2010, 49th IEEE Conference on Decision and Control (CDC).

[5]  U. Shanbhag,et al.  On the characterization of solution sets of smooth and nonsmooth stochastic Nash games , 2010, Proceedings of the 2010 American Control Conference.

[6]  Eduardo F. Camacho,et al.  Randomized Strategies for Probabilistic Solutions of Uncertain Feasibility and Optimization Problems , 2009, IEEE Transactions on Automatic Control.

[7]  Angelia Nedic,et al.  Asynchronous gossip algorithms for stochastic optimization , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[8]  Angelia Nedic,et al.  Subgradient Methods for Saddle-Point Problems , 2009, J. Optimization Theory and Applications.

[9]  Alexander Shapiro,et al.  Stochastic Approximation approach to Stochastic Programming , 2013 .

[10]  Angelia Nedic,et al.  Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization , 2008, J. Optim. Theory Appl..

[11]  Daniela Pucci de Farias,et al.  Decentralized Resource Allocation in Dynamic Networks of Agents , 2008, SIAM J. Optim..

[12]  A. Juditsky,et al.  Solving variational inequalities with Stochastic Mirror-Prox algorithm , 2008, 0809.0815.

[13]  Houyuan Jiang,et al.  Stochastic Approximation Approaches to the Stochastic Variational Inequality Problem , 2008, IEEE Transactions on Automatic Control.

[14]  Angelia Nedic,et al.  Incremental Stochastic Subgradient Algorithms for Convex Optimization , 2008, SIAM J. Optim..

[15]  Shalabh Bhatnagar,et al.  Adaptive Newton-based multivariate smoothed functional algorithms for simulation optimization , 2007, TOMC.

[16]  James C. Spall,et al.  Feedback and Weighting Mechanisms for Improving Jacobian Estimates in the Adaptive Simultaneous Perturbation Algorithm , 2007, IEEE Transactions on Automatic Control.

[17]  Alexander Shapiro,et al.  The empirical behavior of sampling methods for stochastic programming , 2006, Ann. Oper. Res..

[18]  Warren B. Powell,et al.  Learning Algorithms for Separable Approximations of Discrete Stochastic Optimization Problems , 2004, Math. Oper. Res..

[19]  Rayadurgam Srikant,et al.  The Mathematics of Internet Congestion Control , 2003 .

[20]  Michael C. Fu,et al.  Convergence of simultaneous perturbation stochastic approximation for nondifferentiable optimization , 2003, IEEE Trans. Autom. Control..

[21]  H. Kushner,et al.  Stochastic Approximation and Recursive Algorithms and Applications , 2003 .

[22]  Boris Polyak,et al.  Probabilistic robust design with linear quadratic regulators , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[23]  Giuseppe Carlo Calafiore,et al.  Randomized algorithms for probabilistic robustness with real and complex structured uncertainty , 2000, IEEE Trans. Autom. Control..

[24]  Daniel Ralph,et al.  Smooth SQP Methods for Mathematical Programs with Nonlinear Complementarity Constraints , 1999, SIAM J. Optim..

[25]  John N. Tsitsiklis,et al.  Gradient Convergence in Gradient methods with Errors , 1999, SIAM J. Optim..

[26]  Francisco Facchinei,et al.  A smoothing method for mathematical programs with equilibrium constraints , 1999, Math. Program..

[27]  J. Spall Adaptive stochastic approximation by the simultaneous perturbation method , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[28]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..

[29]  Bernard Delyon,et al.  Accelerated Stochastic Approximation , 1993, SIAM J. Optim..

[30]  Boris Polyak,et al.  Acceleration of stochastic approximation by averaging , 1992 .

[31]  J. Spall Multivariate stochastic approximation using a simultaneous perturbation gradient approximation , 1992 .

[32]  Yuri Ermoliev,et al.  Numerical techniques for stochastic optimization , 1988 .

[33]  C. Z. Wei Multivariate Adaptive Stochastic Approximation , 1987 .

[34]  K. Kiwiel Methods of Descent for Nondifferentiable Optimization , 1985 .

[35]  A. Ruszczynski,et al.  Stochastic approximation method with gradient averaging for unconstrained problems , 1983 .

[36]  H. Robbins,et al.  Adaptive Design and Stochastic Approximation , 1979 .

[37]  A. M. Gupal,et al.  Algorithm for the minimization of discontinuous functions , 1977 .

[38]  D. Bertsekas,et al.  A DESCENT NUMERICAL METHOD FOR OPTIMIZATION PROBLEMS WITH NONDIFFERENTIABLE COST FUNCTIONALS , 1973 .

[39]  H. Kushner,et al.  Extensions of Kestin's Adaptive Stochastic Approximation Method, , 1973 .

[40]  D. Bertsekas Stochastic optimization problems with nondifferentiable cost functionals , 1973 .

[41]  D. Bertsekas Stochastic optimization problems with nondifferentiable cost functionals with an application in stochastic programming , 1972, CDC 1972.

[42]  R. Wets,et al.  L-SHAPED LINEAR PROGRAMS WITH APPLICATIONS TO OPTIMAL CONTROL AND STOCHASTIC PROGRAMMING. , 1969 .

[43]  I. P. Grant,et al.  Problems in Mathematical Physics , 1968 .

[44]  J. H. Venter An extension of the Robbins-Monro procedure , 1967 .

[45]  J. Sacks Asymptotic Distribution of Stochastic Approximation Procedures , 1958 .

[46]  H. Kesten Accelerated Stochastic Approximation , 1958 .

[47]  J. Kiefer,et al.  Stochastic Estimation of the Maximum of a Regression Function , 1952 .

[48]  H. Robbins A Stochastic Approximation Method , 1951 .

[49]  Ankur A. Kulkarni,et al.  Recourse-based stochastic nonlinear programming: properties and Benders-SQP algorithms , 2012, Comput. Optim. Appl..

[50]  T. Ralphs,et al.  Decomposition Methods , 2010 .

[51]  Y. Ermoliev Stochastic Quasigradient Methods , 2009, Encyclopedia of Optimization.

[52]  Shalabh Bhatnagar,et al.  Adaptive multivariate three-timescale stochastic approximation algorithms for simulation based optimization , 2005, TOMC.

[53]  Derong Liu The Mathematics of Internet Congestion Control , 2005, IEEE Transactions on Automatic Control.

[54]  A. Shapiro Monte Carlo Sampling Methods , 2003 .

[55]  F. Facchinei,et al.  Finite-Dimensional Variational Inequalities and Complementarity Problems , 2003 .

[56]  Angelia Nedic,et al.  Subgradient methods for convex minimization , 2002 .

[57]  Angelia NediÄ,et al.  Subgradient methods for convex minimization , 2002 .

[58]  D. Bertsekas,et al.  Convergen e Rate of In remental Subgradient Algorithms , 2000 .

[59]  Vivek S. Borkar,et al.  Distributed Asynchronous Incremental Subgradient Methods , 2001 .

[60]  Boris Polyak Random Algorithms for Solving Convex Inequalities , 2001 .

[61]  Sean P. Meyn,et al.  The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning , 2000, SIAM J. Control. Optim..

[62]  D. Bertsekas Gradient convergence in gradient methods , 1997 .

[63]  Jong-Shi Pang,et al.  Mathematical Programs with Equilibrium Constraints , 2021, Pyomo — Optimization Modeling in Python.

[64]  V. Norkin The Analysis and Optimization of Probability Functions , 1993 .

[65]  Yuri Ermoliev,et al.  Stochastic quasigradient methods. Numerical techniques for stochastic optimization , 1988 .

[66]  Y. Ermoliev Stochastic quasigradient methods and their application to system optimization , 1983 .

[67]  Annabelle McIver,et al.  Programming Methodology , 1974, Lecture Notes in Computer Science.