[PDF] Top 20 Computational models of word learning
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Computational models of word learning
... to learning word-object mappings is to imagine a pool of words and a pool of ...objects. Word learning then consists in establishing links between an element in the word pool and an ... See full document
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A Computational Model of Memory, Attention, and Word Learning
... early word learning, and the factors that may facilitate or hinder this process ...1998). Computational modeling has been critical in this endeavor, by giving precise ac- counts of the possible ... See full document
10
Manifold learning for the emulation of spatial fields from computational models
... manifold learning techniques (kernel PCA [33] and diffusion maps [34]) for GPE in high-dimensional spaces, each with their own challenges in terms of constructing a valid basis and finding an inverse map ... See full document
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Semantic Annotation Aggregation with Conditional Crowdsourcing Models and Word Embeddings
... tion models achieve some of the same early performance advantage seen in their generative counterparts, as well as help them operate on datasets that make semantic ... See full document
10
Surveys: A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena
... Where possible, it is interesting to relate our analysis with previously published measures of reordering based on parallel data. To our knowledge, the most compre- hensive results of this kind are reported by Birch ... See full document
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Chemistry teachers' understanding of models of teaching and learning in practical word
... of models of teaching and learning in practical ...of models of teaching and learning which include ‘meaning of models of teaching and learning’ and ‘type of models of ... See full document
14
Active Learning with Sampling by Uncertainty and Density for Word Sense Disambiguation and Text Classification
... In addition to uncertainty sampling, there is another popular selective sampling scheme, Query-by-committee (Engelson and Dagan, 1999), which generates a committee of classifiers (always more than two classifiers) and ... See full document
8
Word Maturity: Computational Modeling of Word Knowledge
... of word meanings from natural language (as can be evidenced by a broad range of applications from synonym tests to automated essay grading), at rates that resemble those of human learners (Laundauer et al, ...of ... See full document
10
From social learning to culture : mathematical and computational models of cultural evolution
... inhibits learning as the naïve ants are carried upside down and facing backwards, unable to orientate themselves or attend to ...enhanced learning, they proposed that feedback between teacher and pupil ... See full document
316
A Probabilistic Model of Syntactic and Semantic Acquisition from Child Directed Utterances and their Meanings
... SVO word order learnt from increasing amounts of training ...correct word order is learnt very quickly and ...rect word-order rule. The distribution over word orders also exhibits initial ... See full document
11
Experiential, Distributional and Dependency based Word Embeddings have Complementary Roles in Decoding Brain Activity
... general computational word represen- tation models can be as good as sensory-motor based word ...corpus-based models on this ...based word representations to model the mental ... See full document
10
A Probabilistic Model for Learning Multi Prototype Word Embeddings
... language models which usually set up a multi-layer neural network, Word2Vec merely leverages a three- layer neural network to learn word embeddings, resulting in greatly decreased number of parameters and ... See full document
10
Word Embeddings, Analogies, and Machine Learning: Beyond king man + woman = queen
... Table 3: Average accuracy per relation type in BATS per method for SVD1000, GloVe and w2v models. Figure 1 demonstrates variation in performance of 3CosAdd, 3CosAvg and LRCos on GloVe and SVD models by ... See full document
12
Character-Level Language Modeling with Deeper Self-Attention
... a large number of parameters. A recent CNN model for text classification (Conneau et al. 2016) at 29 layers is considered deep in the NLP community. A Sparsely-Gated Mixture-of-Experts Layer (Shazeer et al. 2017) allowed ... See full document
8
Co learning of Word Representations and Morpheme Representations
... in learning word ...between word embeddings and morpheme ...the word embeddings, the morpheme embeddings, and the balancing coefficients ... See full document
10
NNBlocks: A Deep Learning Framework for Computational Linguistics Neural Network Models
... With NNBlocks, the models can be combined in any way wanted. Consider the architecture presented in Figure 4, where an input X is fed to a Multilayer Perceptron, then the results are fed to a MeanSquareError Model ... See full document
5
Computational models of learning and beyond: Symmetries of associative learning
... chological models of associative learning as listed in section 2, we find that they relate to deficien- cies that symmetry could be used to ...associative learning phenomena, refers to a lack of ... See full document
20
Learning Expressive Models for Word Sense Disambiguation
... WSD systems have generally been more suc- cessful in the disambiguation of nouns than other grammatical categories (Mihalcea et al., 2004). A common approach to the disambiguation of nouns has been to consider a wide ... See full document
8
A Word Order Database for Testing Computational Models of Language Acquisition
... Particularly interesting is that contrary to results reported by Niyogi & Berwick (1996) and Sakas & Nishimoto (2002), the SVC and Greediness constraints do help the learner achieve the target in the LDD. The ... See full document
8
Computational Models for the Combination of Advice and Individual Learning
... the learning process should be ...observational learning might also be modeled in the ARC framework by assuming that the options chosen by the major- ity receive additional reinforcements, or by adding ... See full document
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