Results 11 to 20 of about 670,072 (283)
Lexikos, 2012 <p class="AP">Der empirische Gegenstandsbereich der Wörterbuchforschung verändert sich u.a. dadurch, dass neue Wörterbücher erscheinen. Dabei ist ein Trend zu erkennen, dass zunehmend mehr neue Elemente der Wörterbuchform im Vorspann, im ...
Herbert Ernst Wiegand, Rufus H. Gouws
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The Latent Structure of Dictionaries [PDF]
Topics in Cognitive Science, 2016 How many words (and which ones) are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable
Blondin Massé, Alexandre +5 more
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Structure-Aware Classification using Supervised Dictionary Learning [PDF]
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016 In this paper, we propose a supervised dictionary learning algorithm that aims to preserve the local geometry in both dimensions of the data. A graph-based regularization explicitly takes into account the local manifold structure of the data points.
Elad, Michael, Yankelevsky, Yael
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Embedding Structured Dictionary Entries [PDF]
Proceedings of the First Workshop on Insights from Negative Results in NLP, 2020 Previous work has shown how to effectively use external resources such as dictionaries to improve English-language word embeddings, either by manipulating the training process or by applying post-hoc adjustments to the embedding space. We experiment with a multi-task learning approach for explicitly incorporating the structured elements of dictionary ...
Wilson, Steven +3 more
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Analysis of fast structured dictionary learning [PDF]
Information and Inference: A Journal of the IMA, 2019 Abstract Sparsity-based models and techniques have been exploited in many signal processing and imaging applications. Data-driven methods based on dictionary and sparsifying transform learning enable learning rich image features from data and can outperform analytical models.
Ravishankar, Saiprasad +2 more
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Hermes, 2007 Based on a number of general proposals for the structure and contents of dictionary grammars, put forward by Mugdan (Mugdan (1989), and reviews of existing dictionary grammars in a number of dictionaries, the article makes proposals for the structure and
Birger Andersen
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Graph Signal Representation with Wasserstein Barycenters [PDF]
, 2018 In many applications signals reside on the vertices of weighted graphs. Thus, there is the need to learn low dimensional representations for graph signals that will allow for data analysis and interpretation.
Frossard, Pascal, Simou, Effrosyni
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Enhancing MR Image Reconstruction Using Block Dictionary Learning
IEEE Access, 2019 While representing a class of signals in term of sparsifying transform, it is better to use a adapted learned dictionary instead of using a predefined dictionary as proposed in the recent literature.
Shahid Ikram +5 more
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Class-Specific Sparse Principal Component Analysis for Visual Classification
IEEE Access, 2020 Extensive research has demonstrated that dictionary learning is active in improving the performance of the representation based classification. However, dictionary learning suffers from lacking an effective dictionary structure that can well tradeoff the
Fei Pan +3 more
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Onomasticon of a Dialect Speaker: A Lexicographic Project [PDF]
Вопросы ономастики, 2015 The article exposes the conception of a dictionary reflecting the system of proper names of a traditional culture bearer. The dictionary is supposed to focus upon the onomasticon of a dialect speaker retrieved from the oral discourse of one person; it ...
Ekaterina V. Ivantsova
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