1,721,023 research outputs found
Bounds of restricted isometry constants in extreme asymptotics: formulae for Gaussian matrices
No full text1 online resource (PDF, 38 pages, includes illustrations)Bah, Bubacarr; Tanner, Jared. (2011). Bounds of restricted isometry constants in extreme asymptotics: formulae for Gaussian matrices. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/181163
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
Efficient algorithms for compressed sensing and matrix completion
Full text linkCompressed sensing and matrix completion are two new data acquisition techniques whose efficiency is achieved by exploring low dimensional structures in high dimensional data. Despite the combinatorial nature of compressed sensing and matrix completion, there has been significant development of computationally efficient algorithms which can produce accurate desired solutions to these problems. In this thesis, we are concerned with the development of low per iteration computational complexity algorithms for compressed sensing and matrix completion. First, we derive a locally optimal stepsize selection rule for the simplest iterative hard thresholding algorithm for matrix completion, and obtain a simple yet efficient algorithm. It is observed to have average case performance superior in some aspects to other matrix completion algorithms. To balance the fast convergence rates of more sophisticated recovery algorithms with the low per iteration computational cost of simple line-search algorithms, we introduce a family of conjugate gradient iterative hard thresholding algorithms for both compressed sensing and matrix completion. The theoretical results establish recovery guarantees for the restarted and projected variants of the algorithms, while the empirical performance comparisons establish significant computational advantages of the proposed methods over other hard thresholding algorithms. Finally, we introduce an alternating steepest descent method and a scaled variant especially designed for the matrix completion problem based on a simple factorization model of the low rank matrix. The computational efficacy of this method is achieved by reducing the high per iteration computational cost of the second order method and fully exploring the numerical linear algebra structure in the algorithm. Empirical evaluations establish the effectiveness of the proposed algorithms, compared with other state-of-the-art algorithms
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Restricted isometry constants in compressed sensing
Full text linkCompressed Sensing (CS) is a framework where we measure data through a non-adaptive linear
mapping with far fewer measurements that the ambient dimension of the data. This is made
possible by the exploitation of the inherent structure (simplicity) in the data being measured.
The central issues in this framework is the design and analysis of the measurement operator
(matrix) and recovery algorithms. Restricted isometry constants (RIC) of the measurement
matrix are the most widely used tool for the analysis of CS recovery algorithms. The addition
of the subscripts 1 and 2 below reflects the two RIC variants developed in the CS literature,
they refer to the ℓ1-norm and ℓ2-norm respectively.
The RIC2 of a matrix A measures how close to an isometry is the action of A on vectors with
few nonzero entries, measured in the ℓ2-norm. This, and related quantities, provide a mechanism
by which standard eigen-analysis can be applied to topics relying on sparsity. Specifically,
the upper and lower RIC2 of a matrix A of size n × N is the maximum and the minimum
deviation from unity (one) of the largest and smallest, respectively, square of singular values of
all (N/k)matrices formed by taking k columns from A. Calculation of the RIC2 is intractable for
most matrices due to its combinatorial nature; however, many random matrices typically have
bounded RIC2 in some range of problem sizes (k, n,N). We provide the best known bound
on the RIC2 for Gaussian matrices, which is also the smallest known bound on the RIC2 for
any large rectangular matrix. Our results are built on the prior bounds of Blanchard, Cartis,
and Tanner in Compressed Sensing: How sharp is the Restricted Isometry Property?, with
improvements achieved by grouping submatrices that share a substantial number of columns.
RIC2 bounds have been presented for a variety of random matrices, matrix dimensions and
sparsity ranges. We provide explicit formulae for RIC2 bounds, of n × N Gaussian matrices
with sparsity k, in three settings: a) n/N fixed and k/n approaching zero, b) k/n fixed and
n/N approaching zero, and c) n/N approaching zero with k/n decaying inverse logarithmically
in N/n; in these three settings the RICs a) decay to zero, b) become unbounded (or approach
inherent bounds), and c) approach a non-zero constant. Implications of these results for RIC2
based analysis of CS algorithms are presented.
The RIC2 of sparse mean zero random matrices can be bounded by using concentration
bounds of Gaussian matrices. However, this RIC2 approach does not capture the benefits of
the sparse matrices, and in so doing gives pessimistic bounds. RIC1 is a variant of RIC2 where
the nearness to an isometry is measured in the ℓ1-norm, which is both able to better capture
the structure of sparse matrices and allows for the analysis of non-mean zero matrices.
We consider a probabilistic construction of sparse random matrices where each column has
a fixed number of non-zeros whose row indices are drawn uniformly at random. These matrices
have a one-to-one correspondence with the adjacency matrices of fixed left degree expander
graphs. We present formulae for the expected cardinality of the set of neighbours for these
graphs, and present a tail bound on the probability that this cardinality will be less than the
expected value. Deducible from this bound is a similar bound for the expansion of the graph
which is of interest in many applications. These bounds are derived through a more detailed
analysis of collisions in unions of sets using a dyadic splitting technique. This bound allows
for quantitative sampling theorems on existence of expander graphs and the sparse random
matrices we consider and also quantitative CS sampling theorems when using sparse non mean-zero
measurement matrices
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
- …
