1,720,985 research outputs found
On the number of arithmetical operations for finding Fibonacci numbers
No full textAbstractTwo algorithms for finding Fibonacci numbers are presented. They are analyzed both from the worst case and average case point of view. The algorithms allow the number of arithmetical operations needed for solving the problem to be decreased
Structure Preserving Reductions Among Convex Optimization Problems
No full textAbstractIn this paper we introduce the concept of convex optimization problem. Convex optimization problems are studied by giving a formalization of the concept of combinatorial structure, in terms of spectra of approximate solutions, and of reduction which preserves such structure. On this basis a classification of convex NP-optimization problems is introduced and is applied to study the combinatorial structure of several optimization problems associated to well-known NP-complete sets. Conditions on the approximability of such optimization problems are also given and it is shown that structurally isomorphic problems have similar approximability properties
An efficient implicit data structure for relation testing and searching in partially ordered sets
No full textIn this paper, we introduce an implicit data structure which represents a forest-structured partial order to efficiently perform, with respect to time and space, the following operations: 1) testing the relation among two elements (checking whether the two elements are related) and 2) given an element u, searching for its father. The first operation can be performed in constant time, while the second one requires polylog time (logarithmic in the case of bounded degree). The data structure represents the order relation by referring only to internal nodes of the forest, thus achieving in many cases a significant saving in space occupation. Finally, the algorithm is shown to be optimal in a restricted computation model by deriving a lower bound on the space complexity within such a model
Suspiciousness of loading problemsProceedings of International Conference on Neural Networks (ICNN'97)
No full textWe introduce the notion of suspect families of loading problems in the attempt of formalizing situations in which classical learning algorithms based on local optimization are likely to fail (because of local minima or numerical precision problems). We show that any loading problem belonging to a nonsuspect family can be solved with optimal complexity by a canonical form of gradient descent with forced dynamics (i.e., for this class of problems no algorithm exhibits a better computational complexity than a slightly modified form of backpropagation). The analyses of this paper suggest intriguing links between the shape of the error surface attached to parametrical learning systems (like neural networks) and the computational complexity of the corresponding optimization problem. © 1997 IEEE
AN EFFICIENT IMPLICIT DATA STRUCTURE FOR PATH TESTING AND SEARCHING IN ROOTED TREES AND FORESTS
No full textPreserving approximation in the Min-Weighted Set Cover Problem
No full textIn this paper we prove that the approximate solutions to the Min-Weighted Set Cover Problem provided by Chvatal's algorithm are combinatorially k-stable with respect to element insertions. Intuitively speaking, we define an approximate solution as combinatorially k-stable with respect to an update operation if its approximation ratio remains the same even if the problem instance is modified by any sequence of at most k such operations. This implies that, if no more than k updates an performed, the approximation ratio is preserved at no computational cost. In particular, we show that any solution returned by Chvatal's algorithm is combinatorially O(log m)-stable with respect to insertions, where in is the number of items in the instance. Hence, since the approximation ratio O(log m) is optimal, the best level of approximability is preserved
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“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
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