We derive compact representations of BFGS and symmetric rank one matrices for optimization These representations allow us to e ciently implement limitedmemory methods for large constrained optimization problems In particular we discuss how to compute projections of limited memory matrices onto subspaces We also present a compact representation of the matrices generated by Broyden s update for s...

For the operation of the nonstop service systems, some methods have been put to practical use to perform the batch update concurrently with the online entries. However, the whole batch update cannot be executed as a transaction by the conventional methods. So, in the case where a transaction failure occurs in the batch update, there is the problem that the rollback of the update cannot be execu...

A new quasi-Newton scheme for updating a low rank positive semi-definite Hessian approximation is described, primarily for use in sequential quadratic programming methods for nonlinear programming. Where possible the symmetric rank one update formula is used, but when this is not possible a new rank two update is used, which is not in the Broyden family, although invariance under linear transfo...

In this paper we propose a new large-update primal-dual interior point algorithm for P∗( ) linear complementarity problems (LCPs). We generalize Bai et al.’s [A primal-dual interior-point method for linear optimization based on a new proximity function, Optim. Methods Software 17(2002) 985–1008] primal-dual interior point algorithm for linear optimization (LO) problem to P∗( ) LCPs. New search ...

| In cellular wireless networks, paging and user location update are used to deliver calls to mobile users. We propose two new user location update methods. One method which improves the movement based user location update scheme, exploits the locality of user movement patterns. Another method performs distance-based location update based on LA such that it simpliies implementation. To compare ...

Streaming classification with emerging new class is an important problem of great research challenge and practical value. In many real applications, the task often needs to handle large matrices issues such as textual data in the bag-ofwords model and large-scale image analysis. However, the methodologies and approaches adopted by the existing solutions, most of which involve massive distance c...

introduction: a large number of software programs have been used in dentistry for diagnosis and treatment planning to date. however, due to promotion of programming languages and developments in dental sciences, it is necessary to develop and update these softwares. use of softwares for treatment planning for removable partial dentures has been popular for some time and always new softwares hav...

Several methods for updating the ghost cell regions of large, distributed arrays are described and results on their relative efficiencies are presented. It was found that no single algorithm provided optimal performance on all platforms and that the most efficient update depended on the details of the system architecture.

The Newtonian method is a standard iterative method with quadratic convergence rates for solving large optimization problems. The Support Vector Machine problem formulation requires the solution of large datasets, which is ideal for the application of Newtonian methods. We point out that the Sequential Minimal Optimization (SMO) algorithm is a Newtonian Decomposition Method that is popular due ...

In [Barr & Kleisli 2001] we described ?-autonomous structures on two full subcategories of topological abelian groups. In this paper we do the same for sup semilattices except that uniform structures play the role that topology did in the earlier paper.