Results 241 to 250 of about 572,458 (282)
Journal of the Royal Anthropological Institute, EarlyView.Abstract In this paper, we present a foray into the computational study of anthropological texts. Drawing on a corpus of approximately 2,500 articles published in the Journal of the Royal Anthropological Institute (formerly Man) from 1950 to 2018, we discuss selected findings from the deployment of two methods for computational text analysis, namely ...
Kristoffer Albris +4 more
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Journal of the Royal Anthropological Institute, EarlyView.The production‐distribution‐consumption triad has structured how anthropologists understand exchange for roughly a century. This article argues for expanding this triad to include an explicit focus on acquisition – the systems, processes, and practices of acquiring.
Hanna Garth
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Romance Loans in Middle Dutch and Middle English: Retained or Lost? A Matter of Metre1
Transactions of the Philological Society, EarlyView.Abstract Romance words have been borrowed into all medieval West‐Germanic languages. Modern cognates show that the metrical patterns of loans can differ although the Germanic words remain constant: loan words Dutch kolónie, English cólony, German Koloníe compared with Germanic words Dutch wéduwe, English wídow, German Wítwe.
Johanneke Sytsema, Aditi Lahiri
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The Syntactic Status of Subject Clitics: A Problem from Venetan SE‐Constructions
Transactions of the Philological Society, EarlyView.Abstract This article reopens the discussion on the syntax of subject clitics (SCLs) in Venetan dialects by providing a problematic piece of data and outlining its theoretical consequences. New evidence from se‐constructions in Alto Polesine Venetan (APV) shows that SCLs resist a unitary categorisation even within the same dialect group: in varieties ...
Marco Fioratti, Leonardo Russo Cardona
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The Aggrieved Subject: Culture Wars and Recognition Rights
Constellations, EarlyView.
Andrew Fagan
wiley +1 more source
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Alternating Proximal Regularized Dictionary Learning
Neural Computation, 2014We present an algorithm for dictionary learning that is based on the alternating proximal algorithm studied by Attouch, Bolte, Redont, and Soubeyran ( 2010 ), coupled with a reliable and efficient dual algorithm for computation of the related proximity operators.
SALZO, SAVERIO +3 more
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Multi-Modal Convolutional Dictionary Learning
IEEE Transactions on Image Processing, 2022Convolutional dictionary learning has become increasingly popular in signal and image processing for its ability to overcome the limitations of traditional patch-based dictionary learning. Although most studies on convolutional dictionary learning mainly focus on the unimodal case, real-world image processing tasks usually involve images from multiple ...
Fangyuan Gao +4 more
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Parsimonious dictionary learning
2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009Sparse modeling of signals has recently received a lot of attention. Often, a linear under-determined generative model for the signals of interest is proposed and a sparsity constraint imposed on the representation. When the generative model is not given, choosing an appropriate generative model is important, so that the given class of signals has ...
Mehrdad Yaghoobi +2 more
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2021
Dictionary learning is one of classical data-driven ways for linear feature extraction, which finds wide applications in image recovery and classification, audio processing, biomedical signal processing, and data fusion. As its natural extension for multidimensional data, tensor dictionary learning can extract the multilinear features. The optimization
Yipeng Liu, Jiani Liu, Zhen Long, Ce Zhu
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Dictionary learning is one of classical data-driven ways for linear feature extraction, which finds wide applications in image recovery and classification, audio processing, biomedical signal processing, and data fusion. As its natural extension for multidimensional data, tensor dictionary learning can extract the multilinear features. The optimization
Yipeng Liu, Jiani Liu, Zhen Long, Ce Zhu
openaire +1 more source
2018
Sparse representations are linear by construction, a fact that can hinder their use in classification problems. Building vectors of characteristics from the signals to be classified can overcome the difficulties and is automated by employing kernels, which are functions that quantify the similarities between two vectors.
Bogdan Dumitrescu, Paul Irofti
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Sparse representations are linear by construction, a fact that can hinder their use in classification problems. Building vectors of characteristics from the signals to be classified can overcome the difficulties and is automated by employing kernels, which are functions that quantify the similarities between two vectors.
Bogdan Dumitrescu, Paul Irofti
openaire +1 more source