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A frequency-domain approach to the analysis and &sign of a learning control law for linear dynamical systems is presented. In its most simple. version the scheme uses two sqnuatejilters in order to achieve rapid improveme& in a specifid... more
Language games are tools to model some aspects of the social aspects of language and communication. Our approach aims to cover the ground between the elementary naming game and the complex models for social use, for the growth of possibly... more
In this paper, we study identification of parametric Hammerstein systems with FIR linear parts. By a proper normalization and a clever characterization, it is shown that the average squared error cost function for identification can be... more
In this paper we consider optimization problems de ned by a quadratic objective function and a nite number of quadratic inequality constraints. Given that the objective function is bounded over the feasible set, we present a comprehensive... more
This paper introduces a novel hybrid dynamical framework that unifies two disparate mathematical paradigms: memoryless stochastic processes, typified by Markov chains, and memory-retaining deterministic systems, modeled by Fredholm and... more
Anisotropic diffusion is posed as a process of minimizing an energy function. Its global convergence behavior is determined by the shape of the energy surface, and its local behavior is described by an orthogonal decomposition with the... more
In this brief, a modification of Lagrangian networks given in is presented. This modification improves the settling time of the convergence of Lagrangian networks to a stationary point; which is the optimal solution to the nonlinear... more
Spatially periodic complex-valued solutions of the Burgers and KdV-Burgers equations are studied in this paper. It is shown that for any sufficiently large time T , there exists an explicit initial data such that its corresponding... more
Identity and learning: A study on the effect of student-teacher gender matching on learning outcomes
In this paper we examine whether students' and teachers' identity play any role in the learning outcome of students. Specifically, we ask if a student benefits by learning from a teacher of her same gender. Unlike the existing literature... more
1. IFPRI Discussion Papers contain preliminary material and research results. They have been peer reviewed, but have not been subject to a formal external review via IFPRI's Publications Review Committee. They are circulated in order to... more
We consider non-differentiable dynamic optimization problems such as those arising in robotics and subspace tracking. Given the computational constraints and the time-varying nature of the problem, a low-complexity algorithm is desirable,... more
An algorithm for unconstrained non-convex optimization is described, which does not evaluate the objective function and in which minimization is carried out, at each iteration, within a randomly selected subspace. It is shown that this... more
Surrogate models are frequently used in the optimization engineering community as convenient approaches to deal with functions for which evaluations are expensive or noisy, or lack convexity. These methodologies do not typically guarantee... more
We propose a new family of multilevel methods for unconstrained minimization. The resulting strategies are multilevel extensions of high-order optimization methods based on q-order Taylor models (with q ≥ 1) that have been recently... more
This short note considers an efficient variant of the trust-region algorithm with dynamic accuracy proposed and by Conn, as a tool for very high-performance computing, an area where it is critical to allow multi-precision computations for... more
Multi-level methods are widely used for the solution of large-scale problems, because of their computational advantages and exploitation of the complementarity between the involved sub-problems. After a re-interpretation of multi-level... more
An adaptive regularization algorithm using inexact function and derivatives evaluations is proposed for the solution of composite nonsmooth nonconvex optimization. It is shown that this algorithm needs at most O(| log(ǫ)| ǫ -2 )... more
A class of second-order algorithms is proposed for minimizing smooth nonconvex functions that alternates between regularized Newton and negative curvature steps in an iterationdependent subspace. In most cases, the Hessian matrix is... more
An adaptive regularization algorithm using inexact function and derivatives evaluations is proposed for the solution of composite nonsmooth nonconvex optimization. It is shown that this algorithm needs at most O(| log(ǫ)| ǫ -2 )... more
We consider an implementation of the recursive multilevel trust-region algorithm proposed by Gratton, Mouffe, Toint and Weber-Mendonça (2008) for bound-constrained nonlinear problems, and provide numerical experience on multilevel test... more
New approximate secant equations are shown to result from the knowledge of (problem dependent) invariant subspace information, which in turn suggests improvements in quasi-Newton methods for unconstrained minimization. A new limitedmemory... more
Surrogate models are frequently used in the optimization engineering community as convenient approaches to deal with functions for which evaluations are expensive or noisy, or lack convexity. These methodologies do not typically guarantee... more
We propose a new family of multilevel methods for unconstrained minimization. The resulting strategies are multilevel extensions of high-order optimization methods based on q-order Taylor models (with q ≥ 1) that have been recently... more
Two useful measures of the robust stability of the discrete-time dynamical system x k+1 = Ax k are the -pseudospectral radius and the numerical radius of A. The -pseudospectral radius of A is the largest of the moduli of the points in the... more
The ‘critical bite’ in this paper lies in providing evidence to challenge the continued and uncritical application of translation and back-translation methodology by the global standard setters and researchers. We applied a within-subject... more
Conjugate gradient (CG) methods are a popular family of iterative algorithms to solve large-scale nonlinear optimization problems due to appropriate features such as no need to calculate the second-order derivatives, low storage and... more
We introduce a new model algorithm for solving nonlinear programming problems. No slack variables are introduced for dealing with inequality constraints. Each iteration of the method proceeds in two phases. In the first phase, feasibility... more
A model algorithm based on the successive quadratic programming method for solving the general nonlinear programming problem is presented. The objective function and the constraints of the problem are only required to be differentiable... more
A practical algorithm for box-constrained optimization is introduced. The algorithm combines an active-set strategy with spectral projected gradient iterations. In the interior of each face a strategy that deals efficiently with negative... more
Globally convergent trust-region methods for self-consistent field electronic structure calculations
As far as more complex systems are being accessible for quantum chemical calculations, the reliability of the algorithms used becomes increasingly important. Trust-region strategies comprise a large family of optimization algorithms that... more
An Algorithm for Solving Nonlinear Least-Squares Problems with a New Curvilinear Search. We propose a modification of an algorithm introduced by Martiuez (1987) for solving nonlinear least-squares problems. Like in the previous algorithm,... more
An inexact restoration (IR) approach is presented to solve a matricial optimization problem arising in electronic structure calculations. The solution of the problem is the closed-shell density matrix and the constraints are represented... more
We develop a numerical algorithm for solving singularly perturbed onedimensional parabolic convection-diffusion problems. The method comprises a standard finite difference to discretize in temporal direction and Sinc-Galerkin method in... more
We register a random sequence constructed based on Markov processes by switching between them. At two random moments θ1, θ2, where 0 ≤ θ1 ≤ θ2, the source of observations is changed. In effect the number of homogeneous segments is random.... more
CPDP is a class of automata designed for compositional specification/analysis of certain stochastic hybrid processes. We prove equivalence of the stochastic behaviors of CPDPs (newly defined here) and PDPs. With this result we obtain a... more
This paper presents a decentralized controller to drive a team of agents to reach a desired formation in the absence of a global reference frame. Each agent is able to measure its relative position and orientation with respect to its... more
This work presents a new iterative method for reconstructing positron emission tomography (PET) images. Unlike conventional maximum likelihood-expectation maximization (MLEM), this method intends to introduce the fuzzy set principle to... more
When a random field (X t , t ∈ R 2 ) is thresholded on a given level u, the excursion set is given by its indicator 1 [u,∞) (X t ). The purpose of this work is to study functionals (as established in stochastic geometry) of these random... more
Nonmonotone spectral gradient (NSG) techniques are considered for unconstrained optimization of differentiable functions. They combine a nonmonotone step length strategy, that is based on the Grippo-Lampariello-Lucidi nonmonotone line... more
In this two-parts paper we propose a decentralized strategy, based on a game-theoretic formulation, to find out the optimal precoding/multiplexing matrices for a multipoint-to-multipoint communication system composed of a set of wideband... more
This paper considers the noncooperative maximization of mutual information in the Gaussian interference channel in a fully distributed fashion via game theory. This problem has been studied in a number of papers during the past decade for... more
By representing molecules as vectors whose components are their nuclear charges, a theorem that allows to order Born-Oppenheimer energies of sets of isoprotonic-isoelectronic molecules is stated. Upper and lower bounds for these sets are... more
In this paper, we are concerned with the conjugate gradient methods for solving unconstrained optimization problems. It is well-known that the direction generated by a conjugate gradient method may not be a descent direction of the... more
Recently developed, second-order sliding-mode control (2-SMC) algorithms are analyzed to assess their global convergence properties. While standard first-order sliding-mode control (1-SMC) algorithms derive their effectiveness from the... more
In this article the design of a new real-time differentiator featuring global convergence properties is considered. Such a problem is tackled by means of a second-order sliding mode differentiator (2-SMD) with adjustable gain and... more
This paper presents an approach to the fault diagnosis and disturbance observation for the hydraulic vertical three-tank system. An observer is designed which contains a corrective term based on a second-order sliding mode control... more
In a recent article, we introduced a method based on a conic model for unconstrained optimization. The acceleration of the convergence of this method was obtained by choosing more appropriate points in order to apply the conic model. In... more
This paper extends the derivative-free descent method for the nonlinear complementarity problem to the symmetric cone complementarity problem (SCCP). The algorithm is based on the unconstrained implicit Lagrangian reformulation of the... more
In this paper, we introduce a special type of SOC-functions which is a vectorvalued function associated with second-order cone. By using it, we construct a type of smoothing functions which converges to the projection function onto... more