Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 1371 for “"Embedding"”.
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Center-embedding and self-embedding in human language processing
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1995.
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Deep Embedding Kernel
… deep architectures that center around the Deep Embedding Kernel (DEK). In short, DEK is a realization of a kernel function through a newly deep architecture. The mapping in DEK is both implicit (like in kernel methods) and learnable (like in deep learning). Prior to DEK, we proposed a less …
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Event network embedding
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-12-01
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AWE: Attention Word Embedding
Word embedding models learn semantically rich vector representations of words and are widely used to initialize natural processing language (NLP) models. The popular continuous bag-of-words (CBOW) model of word2vec learns a vector embedding by masking a given word in a sentence and then using the …
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Embedding scheme in Java
Extension languages are an important part of modern applications development. Java as a platform does not provide a standard extension language. Scheme is one possible choice as an extension language for Java. There are a variety of techniques for implementing Scheme in Java varying from …
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Embedding SLIP in BCPL.
Thesis: M.S., Massachusetts Institute of Technology, Department of Electrical Engineering, 1969
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A framework for embedding simulation.
… primary outcome was to create a framework for embedding simulation based on the research from the successful case studies and the findings and outcomes from the literature survey and questionnaire. The framework was validated using examples of various cases during the research experience in the …
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Action recognition via sequence embedding
… AT AUTHOR'S REQUEST.] A comb structural exemplar embedding based approach is introduced for action recognition. We propose a new framework to represent an action as a weak classifier pool. During training, firstly, construct a set of static comb structural exemplars from training data; then …
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Re-embedding the global soul
… globalized world at the room scale. I define re-embedding as the "plugging in" of social relationships to local contexts and their recombination across time/space distances in order to establish a sense of continuity and order in events including those not directly within the perceptual …
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Embedding Story in the Common Core
This article addresses the Common Core Standards' focus on informational texts. It suggests that using informational texts that build arguments and information with narrative structure will create an engaging and effective classroom experience for students caught in this shift of standards.
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Polyelectrolyte complexes embedding reduced graphite oxide
L'abstract è presente nell'allegato / the abstract is in the attachment
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The book embedding of ordered sets
… a certain objective cost is optimized. In a book embedding for an ordered set, the elements are embedded on the spine of the book to form a linear extension. The pagenumber is the minimum number of pages needed to draw the edges as simple curves such that edges drawn in the same page do not …
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Exploring embedding vectors for emotion detection
… in order to detect emotions. While the word embedding vectors like Word2Vec have been successfully employed in many NLP approaches, the word mover’s distance (WMD) is a method introduced recently to calculate the distance between two documents based on the embedded words. This thesis is …
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Embedding the New York Stock Exchange
… where T is a suitable delay and DE is the embedding dimension. The observed phase space will be shown to be chaotic in its behavior and a reconstructed attractor in the phase space will provide us with predictions of future the stock market prices. All algorithms for computation are written …
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Graph Embedding and Nonlinear Dimensionality Reduction
… analysis (PCA) have been applied to many graph embedding and dimensionality reduction tasks. These methods aim to find low-dimensional representations of data that preserve its inherent structure. However, these methods often perform poorly when applied to data which does not lie exactly near a …
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Post-processing Techniques for Word Embedding
Word embedding has been a significant breakthrough in natural language processing (NLP). Although word representation has improved remarkably and resulted in better performance in downstream NLP applications, interpretability of word embeddings remains a challenge. Post-processing techniques have …
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Embedding problems in graphs and hypergraphs
The first part of this thesis concerns perfect matchings and their generalisations. We determine the minimum vertex degree that ensures a perfect matching in a 3-uniform hypergraph, thereby answering a question of Hàn, Person and Schacht. We say that a graph \(G\) has a perfect \(H\)-packing (also …
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Embedding Problems for Graphs and Hypergraphs
… theory. I will give full proofs of three new embedding results, two for graphs and one for hypergraphs. I will also discuss the regularity lemma for graphs and hypergraphs, an important tool which underpins these and many similar embedding results. Finally, I will also discuss graph and …
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Pairwise embedding for event coreference resolution
… features include but are not limited to sentence embeddings, trigger embeddings, and argument type representations. The extracted features are then used to fine-tune a pre-trained language model, BERT (Bidirectional Encoder Representations from Transformers), to perform event coreference …
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