H. Robbins and S. Monro, "A Stochastic Approximation Method," The Annals of Mathematical Statistics, vol. 22, no. 3, pp. 400-407, Sep. 1951.
B. Polyak, Introduction to optimization. Optimization Software, 1987.
H. J. Kushner and G. Yin, Stochastic approximation and recursive algorithms and applications, 2nd ed. Springer-Verlag, 2003, vol. 35.
D. P. Bertsekas and J. N. Tsitsiklis, "Gradient convergence in gradient methods with errors," SIAM Journal on Optimization, vol. 10, no. 3, pp. 627-642, 2000.
J. N. Tsitsiklis, D. P. Bertsekas, and M. Athans, "Distributed asynchronous deterministic and stochastic gradient optimization algorithms," IEEE Transactions on Automatic Control, vol. 31, no. 9, pp. 803-812, Sep. 1986.
Y. Ermoliev, "On the method of generalized stochastic gradients and quasi-Fejer sequences," Cybernetics, vol. 5, no. 2, pp. 208-220, 1972.
F. Yousefian, A. Nedić, and U. V. Shanbhag, "On stochastic gradient and subgradient methods with adaptive steplength sequences," Automatica, vol. 48, no. 1, pp. 56-67, Jan. 2012.
A. Ruszczyński, "Feasible direction methods for stochastic programming problems," Mathematical Programming, vol. 19, no. 1, pp. 220-229, Dec. 1980.
Y. Ermoliev and P. I. Verchenko, "A linearization method in limiting extremal problems," Cybernetics, vol. 12, no. 2, pp. 240-245, 1977.
A. M. Gupal and L. G. Bazhenov, "Stochastic analog of the conjugant-gradient method," Cybernetics, vol. 8, no. 1, pp. 138-140, 1974.
A. Ribeiro, "Ergodic Stochastic Optimization Algorithms for Wireless Communication and Networking," IEEE Transactions on Signal Processing, vol. 58, no. 12, pp. 6369-6386, Dec. 2010.
G. Scutari, F. Facchinei, P. Song, D. P. Palomar, and J.-S. Pang, "Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems," Feb. 2013, submitted to IEEE Transactions on Signal Processing. [Online]. Available: http://arxiv.org/abs/1302.0756
S. Barbarossa, S. Sardellitti, and P. Di Lorenzo, "Distributed detection and estimation in wireless sensor networks," to appear on E-Reference Signal Processing, R. Chellapa and S. Theodoridis, Eds., Elsevier, 2013.
J. Zhang, D. Zheng, and M. Chiang, "The Impact of Stochastic Noisy Feedback on Distributed Network Utility Maximization," IEEE Transactions on Information Theory, vol. 54, no. 2, pp. 645-665, Feb. 2008.
M. Hong and A. Garcia, "Averaged Iterative Water-Filling Algorithm: Robustness and Convergence," IEEE Transactions on Signal Processing, vol. 59, no. 5, pp. 2448-2454, May 2011.
P. Di Lorenzo, S. Barbarossa, and M. Omilipo, "Distributed Sum-Rate Maximization Over Finite Rate Coordination Links Affected by Random Failures," IEEE Transactions on Signal Processing, vol. 61, no. 3, pp. 648-660, Feb. 2013.
D. P. Bertsekas and J. N. Tsitsiklis, Parallel and distr i bute d c omp uta tion : Numerical methods. Prentice Hall, 1989.
S. Sundhar Ram, A. Nedić, and V. V. Veeravalli, "Incremental Stochastic Subgradient Algorithms for Convex Optimization," SIAM Journal on Optimization, vol. 20, no. 2, pp. 691-717, Jan. 2009.
Y. Yang, G. Scutari, and D. P. Palomar, "Stochastic parallel decomposition algorithms of multi-user systems," 2013, in preparation.
K. Srivastava and A. Nedić, "Distributed Asynchronous Constrained Stochastic Optimization," IEEE Journal of Selected Topics in Signal Processing, vol. 5, no. 4, pp. 772-790, Aug. 2011.
S.-J. Kim and G. B. Giannakis, "Optimal Resource Allocation for MIMO Ad Hoc Cognitive Radio Networks," IEEE Transactions on Information Theory, vol. 57, no. 5, pp. 3117-3131, May 2011.
