Stochastic optimization, especially multistage models, is well known to be computationally excruciating. In this paper, we introduce the concept of semi-complete recourse in the context of stochastic programming as a less restrictive condition compared to complete recourse and propose methods for approximating multistage stochastic programs with risk constraints and semi-complete recourse. We e...

where h >  is a stepsize. It is known that if f :RN →RN is Lipschitz continuous and sufficiently smooth, then the sequence {xn} generated by (.) converges to the exact solution of (.) as h→  uniformly over t ∈ [, t̄] for any fixed t̄ > . If we write the function f in the form f (t) = g(t) – t, then differential equation (.) becomes x′ = g(t)– t. Then the equilibrium problem associated w...

We introduce two approaches to analyses of Borel sum rules. In the first method, we analyze the sum rules in the limit M2 → ∞. Here, the sum rules become very sensitive to the chosen threshold s0. We fix the threshold by setting the daughter sum rule equal to the meson mass in this limit. The second method introduces a Borel mass dependent threshold s0(M 2). We choose functions s0(M 2) such, th...

In a recent article, the authors (Miller & Shettleworth, 2007) showed how the apparently exceptional features of behavior in geometry learning ("reorientation") experiments can be modeled by assuming that geometric and other features at given locations in an arena are learned competitively as in the Rescorla-Wagner model and that the probability of visiting a location is proportional to the tot...

Recently, we described a fast self-organizing algorithm for embedding a set of objects into a low-dimensional Euclidean space in a way that preserves the intrinsic dimensionality and metric structure of the data [Proc. Natl. Acad. Sci. U.S.A. 99 (2002) 15869-15872]. The method, called stochastic proximity embedding (SPE), attempts to preserve the geodesic distances between the embedded objects,...

This paper proposes a modified single-objective binary cuckoo search for association rule mining (MBCS-ARM). The proposed algorithm includes a novel representations of individuals, which tackles the problems of large dimensionality with an increasing number of attributes. The MBCS-ARM also supports the mining of rules, where intervals of attributes can either be negative or positive. It uses an...

<p>This work presents an adjustment mechanism with the sliding modes technique to design a proportional derivative (PD) controller adaptive gains. The objective and contribution are robust in presence of unknown not modeled perturbations system; this perturbation can be considered wind gusts. is designed MIT rule gradient method mode theory. PD obtained applied regulate unmanned fixed-win...