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作者：Ejov, V; Filar, JA; Nguyen, MT
作者单位：University of South Australia; Defence Science & Technology
摘要：We consider the Hamiltonian cycle problem embedded in a singularly perturbed Markov decision process. We also consider a functional on the space of deterministic policies of the process that consists of the (1,1)-entry of the fundamental matrices of the Markov chains induced by the same policies. We show that when the perturbation parameter, epsilon, is less than or equal to 1/N-2, the Hamiltonian cycles of the directed graph are precisely the minimizers of our functional over the space of det...
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作者：Lim, AEB
作者单位：University of California System; University of California Berkeley
摘要：This paper concerns the, problems of quadratic hedging and pricing, and mean-variance portfolio selection in an incomplete market setting with continuous trading, multiple assets, and Brownian information. In particular, we assume throughout that the parameters describing the market model may be random processes. We approach these problems from the perspective of linear-quadratic (LQ) optimal control and backward stochastic differential equations (BSDEs); that is, we focus on the so-called sto...
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作者：Carr, R
作者单位：United States Department of Energy (DOE); Sandia National Laboratories
摘要：The problem of separating a class of inequalities that are valid for the symmetric traveling salesman problem (STSP) consists of devising an efficient method that, given a fractional point x* for a relaxation of the STSP, either finds an inequality in the given class of STSP inequalities that is violated by x* or determines that there are no such violated inequalities. We can define important classes of STSP inequalities by performing Naddef's and Rinaldi's (1993) node-lifting operation on STS...
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作者：Tseng, P
作者单位：University of Washington; University of Washington Seattle
摘要：The EM algorithm is a popular method for maximum likelihood estimation from incomplete. data. This method may be viewed as a proximal point method for maximizing the log-likelihood function using an integral form of the Kullback-Leibler distance function. Motivated by this interpretation, we consider a proximal point method using an integral form of entropy-like distance function. We give a convergence analysis of the resulting proximal point method in the case where the cluster points lie in ...
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作者：Auslender, A; Teboulle, M
作者单位：Universite Claude Bernard Lyon 1; Tel Aviv University
摘要：We extend epsilon-subgradient descent methods for unconstrained nonsmooth convex minimization to constrained problems over polyhedral sets, in particular over R-+(p). This is done by replacing the usual squared quadratic regularization term used in subgradient schemes by the logarithmic-quadratic distancelike function recently introduced by the authors. We then obtain interior epsilon-subgradient descent methods, which allow us to provide a natural extension of bundle methods and Polyak's subg...
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作者：Ng, KF; Zheng, XY
作者单位：Chinese University of Hong Kong; Yunnan University
摘要：In terms of various derivatives such as contingent derivative and Dini-derivative, we give a series of characterizations of error bounds for convex multifunctions defined on Banach spaces, extending Lewis and Pang's result on a characterization of the existence of global error bounds for approximate solutions of convex inequalities in Euclidean spaces. Applications are given not only to improve some known results but also to provide new results on the existence of error bounds for not necessar...
