We propose a probabilistic approach for estimating parameters of an option pricing model from a set of observed option prices. Our approach is based on a stochastic optimization algorithm which generates a random sample from the set of global minima of the in-sample pricing error and allows for the existence of multiple global minima. Starting from an IID population of candidate solutions drawn...

We have explored the chemical space of BAl4Mg?/0/+ for first time and theoretically characterized several isomers with interesting bonding patterns. used intuition a cluster building method based on tabu-search algorithm implemented in Python program aggregation reaction (PyAR) to obtain maximum number possible stationary points. The global minimum geometries anion (1a) cation (1c) contain plan...

Differential evolution (DE) is a population-based and stochastic search algorithm of evolutionary computation that offers three major advantages: it finds the global minimum regardless of the initial parameter values, it involves fast convergence, and it uses few control parameters. This work presents a global optimization algorithm based on DE approaches combined with local search using the im...

In this paper we propose some new ideas for tracking multiple moving objects by the propagation of curves. We assume a static observer, as well as the existence of a background reference frame. The tracking is performed using an improved Geodesic Active Contour model that incorporates boundary-based and region-based motion information. This model is called a Geodesic Active Region model. Initia...

The infrared (IR) spectrum of protonated azulene (AzuH(+), C(10)H(9)(+)) has been measured in the fingerprint range (600-1800 cm(-1)) by means of IR multiple photon dissociation (IRMPD) spectroscopy in a Fourier transform ion cyclotron resonance mass spectrometer equipped with an electrospray ionization source using a free electron laser. The potential energy surface of AzuH(+) has been charact...

A novel staged continuous Tabu search (SCTS) algorithm is proposed for solving global optimization problems of multi-minima functions with multi-variables. The proposed method comprises three stages that are based on the continuous Tabu search (CTS) algorithm with different neighbor-search strategies, with each devoting to one task. The method searches for the global optimum thoroughly and effi...

Solutions to non-linear least squares problems play an essential role in structure and motion problems in computer vision. The predominant approach for solving these problems is a Newton like scheme which uses the hessian of the function to iteratively find a local solution. Although fast, this strategy inevitably leeds to issues with poor local minima and missed global minima. In this paper ra...