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 12 of 12 for “"distributed representations"”.
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Injecting Inductive Biases into Distributed Representations of Text
Distributed real-valued vector representations of text (a.k.a. embeddings), learned by neural networks, encode various (linguistic) knowledge. To encode this knowledge into the embeddings the common approach is to train a large neural network on large corpora. There is, however, a growing concern …
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Distributional and relational inductive biases for graph representation learning in biomedicine
… for constructing methods capable of learning distributed representations of graphs. Our second contribution, Pytorch Geometric Temporal, is the first open source representation learning library for dynamic graphs, expanding the scope of research software on graph neural networks that were …
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Textual entailment from image caption denotations
… task of natural language processing. While distributed representations have become a powerful technique for modeling lexical semantics, but they have traditionally relied on ungrounded text corpora to identify semantically similar words. In contrast, this thesis explicitly models the …
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Conditional Neural Language Models for Multimodal Learning and Natural Language Understanding
… conditional neural language model for learning distributed representations of attributes and meta data. Our model allows for contextual word relatedness comparisons through decompositions of a word embedding tensor. Finally we show how we can abstract the skip-gram model for learning word …
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Disentangled representations in neural models
… success of neural network models. However, the distributed representations generated by neural networks are far from ideal. Due to their highly entangled nature, they are difficult to reuse and interpret, and they do a poor job of capturing the sparsity which is present in real-world …
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Content representation in the human medial temporal lobe
… of sensory inputs into complex memory representations is fundamental to human experience; yet, little is known about how this crucial process is achieved. When you meet your friend at the new cafe in town, what part of the brain encodes this novel scene into long term memory? What part …
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A developmental exploration of Chinese reading in a population of early readers: from eye movement control to textual coherence
… the use of semantic similarity measures based on distributed representations of words, sentences, and paragraphs to assess the impact of supra-lexical constraints on eye-movements in beginning readers of Chinese. The main results show that the most likely account of processes underlying eye …
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Data-Driven Language Understanding for Spoken Dialogue Systems
… module is to translate user inputs into accurate representations of the user goal in the form that can be used by the system to interact with the underlying application. The challenges include the modelling of linguistic variation, speech recognition errors and the effects of dialogue context. …
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Structured Deep Neural Networks for Speech Recognition
… data to be well modelled. However, the highly distributed representations associated with these models make it hard to interpret the parameters. The whole neural network is commonly treated a ``black box''. The behaviours of activation functions and the meanings of network parameters are rarely …
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Weakly Supervised Machine Learning for Cyberbullying Detection
… the first goal, we incorporated the efficacy of distributed representations of words and nodes such as deep, nonlinear models. We represent words and users as low-dimensional vectors of real numbers as the input to language-based and user-based classifiers, respectively. The models are trained by …
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Translationese indicators for human translation quality estimation (based on English-to-Russian translation of mass-media texts)
… are also more interpretable than popular distributed representations and can explain linguistic differences between quality categories in human translation. We investigated (i) an extended set of Universal Dependencies-based morphosyntactic features as well as two lexical feature sets …
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Splitting rocks: Learning word sense representations from corpora and lexica
… tagging to text summarization. These representations of linguistic units, such as words or sentences, allow computer applications that work with language to process and manipulate the meaning of text. In particular, a family of models has been successfully developed based on …