4期

最新文章

• Maximum likelihood estimation of hidden Markov processes AI翻译
  作者：Frydman, H; Lakner, P
  作者单位：New York University
  摘要：We consider the process dY(t) = u(t) dt + dW(t), where u is a process not necessarily adapted to F-Y (the filtration generated by the process Y) and W is a Brownian motion. We obtain a general representation for the likelihood ratio of the law of the Y process relative to Brownian measure. This representation involves only one basic filter (expectation of u conditional on observed process Y). This generalizes the result of Kailath and Zakai [Ann. Math. Statist. 42 (1971) 130-140] where it is a...
• Malyshev's theory and JS-queues. Asymptotics of stationary probabilities AI翻译
  作者：Kurkova, IA; Suhov, YM
  作者单位：Sorbonne Universite; University of Cambridge; University of Cambridge
  摘要：Malyshev's theory of asymptotics of stationary probabilities for a random walk in a quarter-plane is extended to cover the case of join-the-shorter-queues.
• On the multiplicity of the maximum in a discrete random sample AI翻译
  作者：Bruss, FT; Grübel, R
  作者单位：Universite Libre de Bruxelles; Leibniz University Hannover
  摘要：Let M-n be the maximum of a sample X-1,..., X-n from a discrete distribution and let W-n be the number of i's, 1 less than or equal to i less than or equal to n, such that X-i = M-n. We discuss the asymptotic behavior of the distribution of Wn as n --> infinity. The probability that the maximum is unique is of interest in diverse problems, for example, in connection with an algorithm for selecting a winner, and has been studied by several authors using mainly analytic tools. We present here an...
• On convergence of the uniform norms for Gaussian processes and linear approximation problems AI翻译
  作者：Hüsler, J; Piterbarg, V; Seleznjev, O
  作者单位：University of Bern; Lomonosov Moscow State University; Umea University
  摘要：We consider the large values and the mean of the uniform norms for a sequence of Gaussian processes with continuous sample paths. The convergence of the normalized uniform norm to the standard Gumbel (or double exponential) law is derived for distributions and means. The results are obtained from the Poisson convergence of the associated point process of exceedances for a general class of Gaussian processes. As an application we study the piecewise linear interpolation of Gaussian processes wh...
• Convergent multiple-timescales reinforcement learning algorithms in normal form games AI翻译
  作者：Leslie, DS; Collins, EJ
  作者单位：University of Bristol
  摘要：We consider reinforcement learning algorithms in normal form games. Using two-timescales stochastic approximation, we introduce a model-free algorithm which is asymptotically equivalent to the smooth fictitious play algorithm, in that both result in asymptotic pseudo-trajectories to the flow defined by the smooth best response dynamics. Both of these algorithms are shown to converge almost surely to Nash distribution in two-player zero-sum games and N-player partnership games. However, there a...
• Large-deviations analysis of the fluid approximation for a controllable tandem queue AI翻译
  作者：Gajrat, A; Hordijk, A; Ridder, A
  作者单位：Leiden University - Excl LUMC; Leiden University
  摘要：A fluid approximation gives the main term in the asymptotic expression of the value function for a controllable stochastic network. The policies that have the same asymptotic of their value functions as the value function of the optimal policy are called asymptotically optimal policies. We consider the problem of finding from this set of asymptotically optimal policies a best one in the sense that the next term of its asymptotic expression is minimal. The analysis of this problem is closely co...
• Stability analysis of second-order fluid flow models in a stationary ergodic environment AI翻译
  作者：Rabehasaina, L; Sericola, B
  作者单位：Universite Paris Saclay; Universite de Rennes
  摘要：In this paper, we study the stability of a fluid queue with an infinite-capacity buffer. The input and service rates are governed by a stochastic process, called the environment process, and are allowed to depend on the fluid level in the buffer. The variability of the traffic is modeled by a Brownian motion and a local variance function, which also depends on the fluid level in the buffer. The behavior of this second-order fluid flow model is described by a reflected stochastic differential e...
• Critical random walks on two-dimensional complexes with applications to polling systems AI翻译
  作者：MacPhee, IM; Menshikov, MV
  作者单位：Durham University
  摘要：We consider a time-homogeneous random walk Xi = {xi (t)} on a two-dimensional complex. All of our results here are formulated in a constructive way. By this we mean that for any given random walk we can, with an expression using only the first and second moments of the jumps and the return probabilities for some transient one-dimensional random walks, conclude whether the process is ergodic, null-recurrent or transient. Further we can determine when pth moments of passage times tau(K) to sets ...
• Limits of on/off hierarchical product models for data transmission AI翻译
  作者：Resnick, S; Samorodnitsky, G
  作者单位：Cornell University
  摘要：A hierarchical product model seeks to model network traffic as a product of independent on/off processes. Previous studies have assumed a Markovian structure for component processes amounting to assuming that exponential distributions govern on and off periods, but this is not in good agreement with traffic measurements. However, if the number of factor processes grows and input rates are stabilized by allowing the on period distribution to change suitably, a limiting on/off process can be obt...
• Exponential decay of entropy in the random transposition and Bernoulli-Laplace models AI翻译
  作者：Gao, FQ; Quastel, J
  作者单位：Hubei University; University of Toronto
  摘要：We give bounds on the exponential decay rate of entropy in the random transposition model and the Bernoulli-Laplace model which are independent of the number of sites and the number of particles. This is then used to give a bound on the time to stationarity in the total variation norm.