1,721,006 research outputs found
OVERCOMING KNOWLEDGE SHARING CHALLENGES WITH ONTOLOGY-BASED WEB SERVICES
No full textMaster'sMASTER OF SCIENCE IN COMPUTER SCIENCE1. Dr. Edward Altman, I2R. 2. Assoc. Prof. Lee Wee Sun, SMA Fellow, NU
APPLICATION OF INCREMENTAL MINING METHODS TO IDS
No full textMaster'sMASTER OF SCIENCE IN COMPUTER SCIENCEDissertation Supervisors: 1. Dr. Lee Sin Yeung, Senior Technical Staff, DSO. 2. Assoc. Prof. Lee Wee Sun, SMA Fellow, NUS
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
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
PLANNING UNDER UNCERTAINTY: FROM INFORMATIVE PATH PLANNING TO PARTIALLY OBSERVABLE SEMI-MDPS
Get PDFPh.DDOCTOR OF PHILOSOPH
Stochastic Gradient Trees
Get PDFWe present an algorithm for learning decision trees using stochastic gradient information as the source of supervision. In contrast to previous approaches to gradient-based tree learning, our method operates in the incremental learning setting rather than the batch learning setting, and does not make use of soft splits or require the construction of a new tree for every update. We demonstrate how one can apply these decision trees to different problems by changing only the loss function, using classification, regression, and multi-instance learning as example applications. In the experimental evaluation, our method performs similarly tostandard incremental classification trees, outperforms state of the art incremental regression trees, and achieves comparable performance with batch multi-instance learning methods
Online Learning and Planning of Dynamical Systems Using Gaussian Processes
Get PDFMaster'sMASTER OF SCIENC
Hyperbolic Ordinal Embedding
Get PDFGiven ordinal relations such as the object i is more similar to j than k is to l, ordinal embedding is to embed these objects into a low-dimensional space with all ordinal constraints
preserved. Although existing approaches have preserved ordinal relations in Euclidean
space, whether Euclidean space is compatible with true data structure is largely ignored,
although it is essential to effective embedding. Since real data often exhibit hierarchical
structure, it is hard for Euclidean space approaches to achieve effective embeddings in low
dimensionality, which incurs high computational complexity or overfitting. In this paper we
propose a novel hyperbolic ordinal embedding (HOE) method to embed objects in hyperbolic space. Due to the hierarchy-friendly property of hyperbolic space, HOE can effectively
capture the hierarchy to achieve embeddings in an extremely low-dimensional space. We
have not only theoretically proved the superiority of hyperbolic space and the limitations
of Euclidean space for embedding hierarchical data, but also experimentally demonstrated
that HOE significantly outperforms Euclidean-based methods
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