1,721,040 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Code supporting "Nonsmooth Newton's method: some structure exploitation"
No full text<p>This package contains MATLAB, Julia and Python implementations of the structure exploitation method for solving asymmetric linear systems arising from the nonsmooth Newton's method. These codes supplement the paper <em>Nonsmooth Newton's Method: Some Structure Exploitation, </em>by Alberto De Marchi and Matthias Gerdts.</p>
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Augmented Lagrangian and Proximal Methods for Constrained Structured Optimization
No full textThis doctoral thesis aims at investigating and developing numerical methods for finite dimensional constrained structured optimization problems. These provide a modeling framework for a variety of applications, as they offer a simple yet expressive language to formulate a broad class of problems. An algorithm is proposed that interlaces proximal methods and the augmented Lagrangian scheme. Relying on theoretical results, convergence guarantees are established for nonconvex problems. The inner subproblems can be solved by any method for structured optimization and the overall algorithm can be made matrix-free. Illustrative examples show the benefits of constrained structured programs as a modeling tool and of a careful problem formulation. When tested and compared on small to medium-size nonlinear programming benchmark problems, the proposed method prove competitive
against a state-of-the-art solver.
The proposed framework is adopted in the context of switching time optimization for constrained mixed-integer optimal control with switching costs. We describe the reformulation as constrained structured programs via the cardinality function, and discuss possible extensions to deal with more general problems. Then, we prove that this formulation satisfies the assumptions underlying the proximal augmented Lagrangian algorithm. Numerical examples show the filtering action of switching costs, which rules out chattering solutions.
Finally, we develop a primal-dual Newton-type proximal method for convex quadratic programming. This is based on the proposed proximal augmented Lagrangian framework and weaves together the proximal point algorithm and a damped semismooth Newton's method. The outer proximal regularization yields a numerically stable method, and we interpret the proximal operator as the unconstrained minimization of the primal-dual proximal augmented Lagrangian function. The inner tailored Newton's scheme is fast, the linear systems are always solvable, and exact linesearch can be performed. The method handles degenerate problems, provides a mechanism for infeasibility detection, and exploits warm starting, while requiring only convexity. Numerical results against full-fledged solvers demonstrate our method is robust and efficient.
All proposed algorithms are implemented in software packages that allow for the generic, efficient solution of problems using the methods developed in this thesis
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Limited Memory BFGS-Verfahren für dünnbesetzte und hochdimensionale nichtlineare Optimierungsprobleme
No full textOptimization-based control systems are used in many areas of application, including aerospace engineering, economics, robotics and automotive engineering. This work was motivated by the demand for a large-scale sparse solver for this problem class. The sparsity property of the problem is used for the computational efficiency regarding performance and memory consumption. This includes an efficient storing of the occurring matrices and vectors and an appropriate approximation of the Hessian matrix, which is the main subject of this work. Thus, a so-called the limited memory BFGS method has been developed. The limited memory BFGS method, has been implemented in a software library for solving the nonlinear optimization problems, WORHP. Its solving performance has been tested on different optimal control problems and test sets
On the concepts of quality for local solutions of nonlinear programs
No full textThis thesis covers the topic of assessing the quality of local solutions in both standard and parametric nonlinear programming.
From a theoretical perspective, a formal definition of a quality criterion for local solutions of nonlinear programs is introduced, and the notions of primary and secondary quality criteria are distinguished. Since the primary criterion is inherently associated with the optimality of local solutions, the main focus is on secondary criteria. In particular, over 25 existing secondary quality criteria are systematically reviewed and analyzed. These criteria, arising in both non-parametric and parametric nonlinear programming, are derived from the fields of dynamical systems, robust optimization, stochastic optimization, and parametric sensitivity analysis.
From an applied perspective, two novel secondary quality criteria are proposed: the maximum radius of attraction (MRoA) and the parametric stability score (PSS). MRoA is a measure of quality for local solutions of non-parametric nonlinear programs. It is defined as the radius of the largest ball centered at a local solution such that a given optimization algorithm, once initialized inside that ball, is guaranteed never to escape it and is expected to converge to the same solution. PSS, in turn, quantifies the quality of local solutions of parametric nonlinear programs. It is defined as the maximum magnitude of a perturbation of the nominal parameter, such that for any smaller perturbation, the solutions and corresponding optimal costs of the nominal and perturbed problems remain within prescribed distances. The utility of the PSS concept is demonstrated using an optimal control problem for accomplishing the swing-up maneuver of the pendulum on a cart system.
For both proposed criteria, connections to the field of online optimization are established, emphasizing their potential to support informed decision-making
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