A major challenge for stochastic optimization is the cost of updating model parameters especially when the number of parameters is large. Updating parameters frequently can prove to be computationally or monetarily expensive. In this paper, we introduce an efficient primal-dual based online algorithm that performs lazy updates to the parameter vector and show that its performance is competitive...

In this paper, we present an application of the stochastic calculusto the problem of modeling electrical networks. The filtering problem have animportant role in the theory of stochastic differential equations(SDEs). In thisarticle, we present an application of the continuous Kalman-Bucy filter for a RLcircuit. The deterministic model of the circuit is replaced by a stochastic model byadding a ...

this paper introduces a numerical method for solving the vasicek model by using a stochastic operational matrix based on the triangular functions (tfs) in combination with the collocation method. the method is stated by using conversion the vasicek model to a stochastic nonlinear system of $2m+2$ equations and $2m+2$ unknowns. finally, the error analysis and some numerical examples are provided...

Biological reaction networks often contain what might be called ‘hub molecules’, which are involved in many reactions. For example, ATP is commonly consumed and produced. When reaction networks contain molecules like ATP, they are difficult to efficiently simulate, because every time such a molecule is consumed or produced, the propensities of numerous reactions need to be updated. In order to ...

this paper studies a maintenance policy for a system composed of two components, which are subject to continuous deterioration and consequently stochastic failure. the failure of each component results in the failure of the system. the components are inspected periodically and their deterioration degrees are monitored. the components can be maintained using different maintenance actions (repair...

The iterative learning control (ILC) problem is addressed in this paper for stochastic linear systems with random data dropout modeled by a Bernoulli random variable. Both intermittent updating scheme and successive updating scheme are provided on the basis of the available tracking information only and shown to be convergent to the desired input almost certainly. In the intermittent updating s...

We consider the stochastic multi-armed bandit problem with unknown horizon. We present a randomized decision strategy which is based on updating a probability distribution through a stochastic mirror descent type algorithm. We consider separately two assumptions: nonnegative losses or arbitrary losses with an exponential moment condition. We prove optimal (up to logarithmic factors) gap-free bo...