The method of conjugate directions provides a very effective way to optimize large, deterministic systems by gradient descent. In its standard form, however, it is not amenable to stochastic approximation of the gradient. Here we explore ideas from conjugate gradient in the stochastic (online) setting, using fast Hessian-gradient products to set up low-dimensional Krylov subspaces within indivi...

In this paper, stochastic comparisons for k -out-ofN ( F ) system with random numbers of identical components are studied. The lifetime of k -out-ofN ( F ) system corresponds to the kth order statistic of random numbers of independent identically distributed random variables. Characterizations based on some stochastic orders, for example, star order, hazard rate order and reversed hazard order ...

The method of conjugate gradients provides a very effective way to optimize large, deterministic systems by gradient descent. In its standard form, however, it is not amenable to stochastic approximation of the gradient. Here we explore ideas from conjugate gradient in the stochastic (online) setting, using fast Hessian-gradient products to set up low-dimensional Krylov subspaces within individ...

We study a class of discounted infinite horizon stochastic games with strategic complementarities. Using monotone operators on the space of values and strategies, we prove existence of a Stationary Markov Nash equilibrium under different set of assumptions than Curtat (1996), Amir (2002, 2005) or Nowak (2007) via constructive methods. In addition, we provide monotone comparative statics results...

The first laboratory confirmation of stochastic growth theory is reported. Floating potential fluctuations are measured in a vacuum arc centrifuge using a Langmuir probe. Statistical analysis of the energy density reveals a lognormal distribution over roughly 2 orders of magnitude, with a high-field nonlinear cutoff whose spatial dependence is consistent with the predicted eigenmode profile. Th...

A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.

To that end, the collaborative action will bring together specialists: of discrete-event systems and stochastic orders on the one hand, and of queueing, networking and manufacturing applications on the other hand. By analyzing several concrete problems which cannot presently be handled by known methods, it is hoped that new proof techniques, presumably based on stochastic ordering concepts, wil...

We present a new algorithm based on Wiener-Hermite functionals combined with Fourier collocation to solve the advection equation with stochastic transport velocity. We develop different stategies of representing the stochastic input, and demonstrate that this approach is orders of magnitude more efficient than Monte Carlo simulations for comparable accuracy.

We consider an example network where we compute the bounds on cell loss rates. The stochastic bounds for these loss rates using simple arguments lead to models easier to solve. We proved, using stochastic orders, that the loss rates of these easier models are really the bounds of our original model. For ill-balanced configurations these models give good estimates of loss rates.

“Symplectic” schemes for stochastic Hamiltonian dynamical systems are formulated through “composition methods or operator splitting methods ” proposed by Misawa 2001 . In the proposed methods, a symplectic map, which is given by the solution of a stochastic Hamiltonian system, is approximated by composition of the stochastic flows derived from simpler Hamiltonian vector fields. The global error...