102,634 research outputs found

    In Banc Procedures in the United States Courts of Appeals

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    Local Variation as a Statistical Hypothesis Test

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    The goal of image oversegmentation is to divide an image into several pieces, each of which should ideally be part of an object. One of the simplest and yet most effective oversegmentation algorithms is known as local variation (LV) (Felzenszwalb and Huttenlocher 2004). In this work, we study this algorithm and show that algorithms similar to LV can be devised by applying different statistical models and decisions, thus providing further theoretical justification and a well-founded explanation for the unexpected high performance of the LV approach. Some of these algorithms are based on statistics of natural images and on a hypothesis testing decision; we denote these algorithms probabilistic local variation (pLV). The best pLV algorithm, which relies on censored estimation, presents state-of-the-art results while keeping the same computational complexity of the LV algorithm

    Schwarz Iterative Methods: Infinite Space Splittings

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    We prove the convergence of greedy and randomized versions of Schwarz iterative methods for solving linear elliptic variational problems based on infinite space splittings of a Hilbert space. For the greedy case, we show a squared error decay rate of O((m+1)−1)O((m+1)^{-1}) for elements of an approximation space A1\mathcal{A}_1 related to the underlying splitting. For the randomized case, we show an expected squared error decay rate of O((m+1)−1)O((m+1)^{-1}) on a class A∞π⊂A1\mathcal{A}_{\infty}^{\pi}\subset \mathcal{A}_1 depending on the probability distribution.Comment: Revised version, accepted in Constr. Appro

    Stochastic subspace correction methods and fault tolerance

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    We present convergence results in expectation for stochastic subspace correction schemes and their accelerated versions to solve symmetric positive-definite variational problems, and discuss their potential for achieving fault tolerance in an unreliable compute network. We employ the standard overlapping domain decomposition algorithm for PDE discretizations to discuss the latter aspect.Comment: 33 pages, 6 figure

    What Catholic educators can learn from the radical Christianity and critical pedagogy of Don Lorenzo Milani

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    This paper exposes some of the ideas expressed or associated with the work of don Lorenzo Milani and the School of Barbiana and discusses them in the light of the teachings of the gospels. It draws out the ramifications of these ideas for a critical education in the Christian spirit. The focus throughout is on education for social justice.peer-reviewe
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