We consider implicit integration methods for the numerical solution of sti initial-value problems. In applying such methods, the implicit relations are usually solved by Newton iteration. However, it often happens that in subintervals of the integration interval the problem is nonsti or mildly sti with respect to the stepsize. In these nonsti subintervals, we do not need the (expensive) Newton ...

‎in this paper‎, ‎we propose a feasible interior-point method for‎ ‎convex quadratic programming over symmetric cones‎. ‎the proposed algorithm relaxes the‎ ‎accuracy requirements in the solution of the newton equation system‎, ‎by using an inexact newton direction‎. ‎furthermore‎, ‎we obtain an‎ ‎acceptable level of error in the inexact algorithm on convex‎ ‎quadratic symmetric cone programmin...

In this work, we present how domain modeling and Programming by Example techniques can be combined to carry through a EUD approach. Our techniques are based on detecting iteration patterns from user monitoring as well as extracting knowledge about the user interface itself. Combining those, dynamic behavior can be characterized, getting maximum amount of semantic at each user step. This approac...

In this paper, we shall introduce a Jungck-Noor three-step iteration process to establish a strong convergence result for a pair of nonselfmappings in an arbitrary Banach space by employing a general contractive condition. Our result is a generalization and extension of a multitude of results. In particular, it is a generalization and extension of some of the results of Kannan [11, 12], Rhoades...

The purpose of this paper is to establish some strong convergence theorems of three-step iteration process with errors for approximating common fixed points for a finite family of asymptotically quasi-nonexpansive mappings in the intermediate sense in the setting of convex metric spaces. The results obtained in this paper generalize, improve and unify some main results of [1]-[7], [9]-[11], [13...

The simple Lanczos process is very eeective for nding a few extreme eigenvalues of a large symmetric matrix. The main task in each iteration step consists in evaluating a matrix-vector product. It is shown in this paper how to apply a fast wavelet-based product in order to speed up computations. Some numerical results are given for the simple case of the Harmonic Oscillator.

The purpose of this paper is to establish some weak convergence theorems of modified two-step iteration process with errors for two asymptotically quasi-nonexpansive non-self mappings in the setting of real uniformly convex Banach spaces if E satisfies Opial’s condition or the dual E∗ of E has the Kedec-Klee property. Our results extend and improve some known corresponding results from the exis...

Motivated by a numerical example which shows that a feasible version of Mehrotra’s original predictor-corrector algorithm might be inefficient in practice, Salahi et al., proposed a so-called safeguard based variant of the algorithm that enjoys polynomial iteration complexity while its practical efficiency is preserved. In this paper we analyze the same Mehrotra’s algorithm from a different per...

Approximate value iteration methods for reinforcement learning (RL) generalize experience from limited samples across large stateaction spaces. The function approximators used in such methods typically introduce errors in value estimation which can harm the quality of the learned value functions. We present a new batch-mode, off-policy, approximate value iteration algorithm called Trajectory Fi...