567 research outputs found

    Improved Approximation Algorithms for the Min-Max Selecting Items Problem

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    We give a simple deterministic O(logK/loglogK)O(\log K / \log\log K) approximation algorithm for the Min-Max Selecting Items problem, where KK is the number of scenarios. While our main goal is simplicity, this result also improves over the previous best approximation ratio of O(logK)O(\log K) due to Kasperski, Kurpisz, and Zieli\'nski (Information Processing Letters (2013)). Despite using the method of pessimistic estimators, the algorithm has a polynomial runtime also in the RAM model of computation. We also show that the LP formulation for this problem by Kasperski and Zieli\'nski (Annals of Operations Research (2009)), which is the basis for the previous work and ours, has an integrality gap of at least Ω(logK/loglogK)\Omega(\log K / \log\log K)

    An Interval Extension Based on Occurrence Grouping: Method and Properties

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    In interval arithmetics, special care has been brought to the definition of interval extension functions that compute narrow interval images. In particular, when a function f is monotonic w.r.t. a variable in a given domain, it is well-known that the monotonicity-based interval extension of f computes a sharper (interval) image than the natural interval extension does. This paper presents a so-called ''occurrence grouping'' interval extension [f]_{og} of a function f. When f is not monotonic w.r.t. a variable x in a given domain, we try to transform f into a new function f^{og} that is monotonic w.r.t. two subsets x_a and x_b of the occurrences of x: f^{og} is increasing w.r.t. x_a and decreasing w.r.t. x_b. [f]_{og} is the interval extension by monotonicity of f^{og} and produces a sharper interval image than the natural extension does. For finding a good occurrence grouping, we propose a linear program and an algorithm that minimize a Taylor-based over-estimate of the image diameter of [f]_{og}. Experiments show the benefits of this new interval extension for solving systems of nonlinear equations.L'analyse d'intervalles a proposé plusieurs extensions aux intervalles qui essaient de calculer des images étroites des fonctions. En particulier, quand une fonction f est monotone par rapport à une variable sur un domaine donné, il est bien connu que l'extension aux intervalles par monotonie de f permet de calculer un intervalle image plus étroit que l'extension naturelle. Cet article présente une nouvelle extension aux intervalles d'une fonction f appelée regroupement d'occurrences et notée [f]_{og}. Quand f n'est pas monotone par rapport à une variable x sur un domaine donné, nous essayons de transformer f en une nouvelle fonction f^{og} qui est monotone par rapport à deux sous-ensembles x_a et x_b des occurrences de x : f^{og} est croissante par rapport à x_a et décroissante par rapport à x_b. [f]_{og} est l'extension aux intervalles par monotonie de f^{og} et produit une image plus étroite que l'extension naturelle. Pour trouver un bon regroupement d'occurrences, nous proposons un programme linéaire et un algorithme qui minimisent une surestimation du diamètre de l'image de [f]_{og} basée sur une forme de Taylor de f. Finalement, des expérimentations montrent les avantages de cette nouvelle extension pour la résolution de systèmes d'équations non linéaires

    Provable randomized rounding for minimum-similarity diversification

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    When searching for information in a data collection, we are often interested not only in finding relevant items, but also in assembling a diverse set, so as to explore different concepts that are present in the data. This problem has been researched extensively. However, finding a set of items with minimal pairwise similarities can be computationally challenging, and most existing works striving for quality guarantees assume that item relatedness is measured by a distance function. Given the widespread use of similarity functions in many domains, we believe this to be an important gap in the literature. In this paper we study the problem of finding a diverse set of items, when item relatedness is measured by a similarity function. We formulate the diversification task using a flexible, broadly applicable minimization objective, consisting of the sum of pairwise similarities of the selected items and a relevance penalty term. To find good solutions we adopt a randomized rounding strategy, which is challenging to analyze because of the cardinality constraint present in our formulation. Even though this obstacle can be overcome using dependent rounding, we show that it is possible to obtain provably good solutions using an independent approach, which is faster, simpler to implement and completely parallelizable. Our analysis relies on a novel bound for the ratio of Poisson-Binomial densities, which is of independent interest and has potential implications for other combinatorial-optimization problems. We leverage this result to design an efficient randomized algorithm that provides a lower-order additive approximation guarantee. We validate our method using several benchmark datasets, and show that it consistently outperforms the greedy approaches that are commonly used in the literature.Peer reviewe

    A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones

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    Fully-autonomous miniaturized robots (e.g., drones), with artificial intelligence (AI) based visual navigation capabilities are extremely challenging drivers of Internet-of-Things edge intelligence capabilities. Visual navigation based on AI approaches, such as deep neural networks (DNNs) are becoming pervasive for standard-size drones, but are considered out of reach for nanodrones with size of a few cm2{}^\mathrm{2}. In this work, we present the first (to the best of our knowledge) demonstration of a navigation engine for autonomous nano-drones capable of closed-loop end-to-end DNN-based visual navigation. To achieve this goal we developed a complete methodology for parallel execution of complex DNNs directly on-bard of resource-constrained milliwatt-scale nodes. Our system is based on GAP8, a novel parallel ultra-low-power computing platform, and a 27 g commercial, open-source CrazyFlie 2.0 nano-quadrotor. As part of our general methodology we discuss the software mapping techniques that enable the state-of-the-art deep convolutional neural network presented in [1] to be fully executed on-board within a strict 6 fps real-time constraint with no compromise in terms of flight results, while all processing is done with only 64 mW on average. Our navigation engine is flexible and can be used to span a wide performance range: at its peak performance corner it achieves 18 fps while still consuming on average just 3.5% of the power envelope of the deployed nano-aircraft.Comment: 15 pages, 13 figures, 5 tables, 2 listings, accepted for publication in the IEEE Internet of Things Journal (IEEE IOTJ

    Chapter 8 Learning of written language

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    The deaf and hard-of-hearing sometimes experience constraints that differ from those of hearing people; plus, when this physiological state (deafness) coincides with other disorders, learning to write becomes exceptionally difficult. The main interest of this chapter includes the strategies that hard-of-hearing and deaf (non-hearing) children devise to learn to write and how they use writing in the development of knowledge in the Haitian context. It is a matter of understanding how these children manage to learn to read and write, and of analyzing impacts of judgements on their school performances. As deafness, seen in particular from the angle of sensorimotor disorder is described as phenomenon that impose social specific limitations on children, this chapter is to study the impacts of pedagogical practices on the learning process of written language. The deafness as a characteristic of a community of people that are culturally and linguistically different community, is notably studied

    Chapter 8 Learning of written language

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    The deaf and hard-of-hearing sometimes experience constraints that differ from those of hearing people; plus, when this physiological state (deafness) coincides with other disorders, learning to write becomes exceptionally difficult. The main interest of this chapter includes the strategies that hard-of-hearing and deaf (non-hearing) children devise to learn to write and how they use writing in the development of knowledge in the Haitian context. It is a matter of understanding how these children manage to learn to read and write, and of analyzing impacts of judgements on their school performances. As deafness, seen in particular from the angle of sensorimotor disorder is described as phenomenon that impose social specific limitations on children, this chapter is to study the impacts of pedagogical practices on the learning process of written language. The deafness as a characteristic of a community of people that are culturally and linguistically different community, is notably studied

    What is Humanism?

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    This is the text of The Lindley Lecture for 1977, given by Georg Henrik (1916-2003), a Finnish philosopher

    From Jook Joints to Sisterspace: The Role of Nature in Lesbian Alternative Environments in the United States

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    Despite the depth and breadth of Catriona Sandilands\u27s groundbreaking Lesbian Separatist Communities and the Experience of Nature, with its emphasis on communities in southern Oregon, Sandilands does not consider her article, published in 2002, to be the last one on the topic. Instead she hopes fervently that other researchers will enter into the ongoing conversation [about queer landscapes) (136). This essay is an answer to her invitation to draw further insight from queer cultures to form alternative, even transformative, cultures of nature (135). It examines the role of place in the history of American lesbians, particularly the role of nonhuman nature in the alternative environments lesbians created and nurtured in their efforts to transcend the sexism, homophobia, violence, materialism, and environmental abuse afflicting mainstream society. Certainly such an investigation supports the challenge, detailed in Katie Hogan\u27s essay in this collection, to the notion of queers as unnatural and against nature. Lesbians\u27 ways of incorporating nonhuman nature into their temporary and permanent communities demonstrate how members of an oppressed minority created safe havens and spaces to be themselves. In addition to offering mainstream society insight into the impact of place on identity, in some instances lesbian communities also provide some important working examples of alternate ways of living on and with the land
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