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    NIPS
    2003
    142views Information Technology» more  NIPS 2003»
    A Holistic Approach to Compositional Semantics: A Connectionist Model and Robot Experiments
    13 years 5 months ago
    A Holistic Approach to Compositional Semantics: A Connectionist Model and Robot Experiments
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    We present a novel connectionist model for acquiring the semantics of a simple language through the behavioral experiences of a real robot. We focus on the “compositionality” ...
    Yuuya Sugita, Jun Tani
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    NIPS
    2003
    160views Information Technology» more  NIPS 2003»
    Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data
    13 years 5 months ago
    Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data
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    Discrete Fourier transforms and other related Fourier methods have been practically implementable due to the fast Fourier transform (FFT). However there are many situations where ...
    Amos J. Storkey
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    NIPS
    2003
    128views Information Technology» more  NIPS 2003»
    Geometric Clustering Using the Information Bottleneck Method
    13 years 5 months ago
    Geometric Clustering Using the Information Bottleneck Method
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    We argue that K–means and deterministic annealing algorithms for geometric clustering can be derived from the more general Information Bottleneck approach. If we cluster the ide...
    Susanne Still, William Bialek, Léon Bottou
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    NIPS
    2003
    113views Information Technology» more  NIPS 2003»
    Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
    13 years 5 months ago
    Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
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    The decision functions constructed by support vector machines (SVM’s) usually depend only on a subset of the training set—the so-called support vectors. We derive asymptotical...
    Ingo Steinwart
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    NIPS
    2003
    107views Information Technology» more  NIPS 2003»
    Bias-Corrected Bootstrap and Model Uncertainty
    13 years 5 months ago
    Bias-Corrected Bootstrap and Model Uncertainty
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    The bootstrap has become a popular method for exploring model (structure) uncertainty. Our experiments with artificial and realworld data demonstrate that the graphs learned from...
    Harald Steck, Tommi Jaakkola
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    NIPS
    2003
    171views Information Technology» more  NIPS 2003»
    A Computational Geometric Approach to Shape Analysis in Images
    13 years 5 months ago
    A Computational Geometric Approach to Shape Analysis in Images
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    We present a geometric approach to statistical shape analysis of closed curves in images. The basic idea is to specify a space of closed curves satisfying given constraints, and e...
    Anuj Srivastava, Xiuwen Liu, Washington Mio, Eric ...
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    NIPS
    2003
    138views Information Technology» more  NIPS 2003»
    Linear Dependent Dimensionality Reduction
    13 years 5 months ago
    Linear Dependent Dimensionality Reduction
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    We formulate linear dimensionality reduction as a semi-parametric estimation problem, enabling us to study its asymptotic behavior. We generalize the problem beyond additive Gauss...
    Nathan Srebro, Tommi Jaakkola
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    NIPS
    2003
    268views Information Technology» more  NIPS 2003»
    Eye Movements for Reward Maximization
    13 years 5 months ago
    Eye Movements for Reward Maximization
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    Recent eye tracking studies in natural tasks suggest that there is a tight link between eye movements and goal directed motor actions. However, most existing models of human eye m...
    Nathan Sprague, Dana H. Ballard
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    NIPS
    2003
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    Unsupervised Context Sensitive Language Acquisition from a Large Corpus
    13 years 5 months ago
    Unsupervised Context Sensitive Language Acquisition from a Large Corpus
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    We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. Th...
    Zach Solan, David Horn, Eytan Ruppin, Shimon Edelm...
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    NIPS
    2003
    144views Information Technology» more  NIPS 2003»
    Warped Gaussian Processes
    13 years 5 months ago
    Warped Gaussian Processes
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    We generalise the Gaussian process (GP) framework for regression by learning a nonlinear transformation of the GP outputs. This allows for non-Gaussian processes and non-Gaussian ...
    Edward Snelson, Carl Edward Rasmussen, Zoubin Ghah...
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