We have used Papanek's 1985 revised edition rather than the original one of 1972 because he made a number of changes from one edition to another, and we wanted to draw on his most current thinking. For a discussion of Papanek's concept of socially…
Papers in Computational Linguistics
Computational Linguistics papers in Linguistics, A
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Fluid Construction Grammar (FCG) is a new linguistic formalism designed to explore in how far a construction grammar approach can be used for handling open-ended grounded dialogue, i.e. dialogue between or with autonomous embodied agents about the…
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Propose le calcul de quadrique a partir de point 3D et le matching de ces dernieres. Marche moyennement. roger
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We explore the implications of an event-based expectancy generation approach to language understanding, suggesting that one useful strategy employed by comprehenders is to generate expectations about upcoming words. We focus on two questions: (1)…
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The Bayesian approach to statistical problems, though fruitful in many ways, has been rather unsuccessful in treating nonparametric problems. This is due primarily to the difficulty in finding workable prior distributions on the parameter space,…
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Evolutionary biologists often wish to explore the impact of a particular historical event (e.g., the origin of a novel morphological trait, an episode of biogeographic dispersal, or the onset of an ecological association) on rates of diversification…
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Bayesian learningmethods have recently been shown to provide an elegant solution to the explorationexploitation trade-off in reinforcement learning. However most investigations of Bayesian reinforcement learning to date focus on the standard Markov…
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We present an efficient, principled, and interpretable technique for inferring module assignments and for identifying the optimal number of modules in a given network. We show how several existing methods for finding modules can be described as…
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We propose a novel approach to learn and recognize natural scene categories. Unlike previous work, it does not require experts to annotate the training set. We represent the image of a scene by a collection of local regions, denoted as codewords…
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Accurate estimates of mitochondrial substitution rates are central to molecular studies of human evolution, but meaningful comparisons of published studies are problematic because of the wide range of methodologies and data sets employed. These…
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Since the experiments of Saffran et al. Saffran, J., Aslin, R., & Newport, E. (1996). Statistical learning in 8-month-old infants. Science, 274, 1926-1928, there has been a great deal of interest in the question of how statistical regularities in…
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ABSTRACT: BACKGROUND: Patterns of species diversity are the result of speciation and extinction processes, and molecular phylogenetic data can provide valuable information to derive their variability through time and across clades. Bayesian Markov…
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Political scientists lack methods to efficiently measure the priorities political actors emphasize in statements. To address this limitation, I introduce a statistical model that attends to the structure of political rhetoric when measuring…
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Two classes of methods have been shown to be useful for resolving lexical ambiguity. The first relies on the presence of particular words within some distance of the ambiguous target word; the second uses the pattern of words and part-of-speech tags…
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Existing word similarity measures are not robust to data sparseness since they rely only on the point estimation of words context profiles obtained from a limited amount of data. This paper proposes a Bayesian method for robust distributional word…
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A standard form of analysis for linguistic typology is the universal implication. These implications state facts about the range of extant languages, such as ``if objects come after verbs, then adjectives come after nouns.'' Such implications are…
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This paper describes a system for unsupervised learning of morphological affixes from texts or word lists. The system is composed of a generative probability model and a search algorithm. Experiments on the Wall Street Journal and the Hansard Corpus…
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A non-parametric Bayesian model is proposed for processing multiple images. The analysis employs image features and, when present, the words associated with accompanying annotations. The model clusters the images into classes, and each image is…
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We propose a non-parametric Bayesian model for unsupervised semantic parsing. Following Poon and Domingos (2009), we consider a semantic parsing setting where the goal is to (1) decompose the syntactic dependency tree of a sentence into fragments,…
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Tree based translation models are a compelling means of integrating linguistic in- formation into machine translation. Syntax can inform lexical selection and reordering choices and thereby improve translation quality. Research to date has focussed…
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