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    IJCNN
    2008
    IEEE
    170views Neural Networks» more  IJCNN 2008»
    Learning adaptive subject-independent P300 models for EEG-based brain-computer interfaces
    14 years 3 months ago
    Learning adaptive subject-independent P300 models for EEG-based brain-computer interfaces
    Download  nsp.i2r.a-star.edu.sg
    Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
    Shijian Lu, Cuntai Guan, Haihong Zhang
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    AAAI
    2007
    123views Intelligent Agents» more  AAAI 2007»
    Recognizing Textual Entailment Using a Subsequence Kernel Method
    13 years 11 months ago
    Recognizing Textual Entailment Using a Subsequence Kernel Method
    Download  www.aaai.org
    We present a novel approach to recognizing Textual nt. Structural features are constructed from abstract tree descriptions, which are automatically extracted from syntactic depend...
    Rui Wang 0005, Günter Neumann
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    ACL
    2008
    135views Computational Linguistics» more  ACL 2008»
    A Single Generative Model for Joint Morphological Segmentation and Syntactic Parsing
    13 years 10 months ago
    A Single Generative Model for Joint Morphological Segmentation and Syntactic Parsing
    Download  staff.science.uva.nl
    Morphologicalprocesses in Semitic languages deliver space-delimited words which introduce multiple, distinct, syntactic units into the structure of the input sentence. These words...
    Yoav Goldberg, Reut Tsarfaty
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    ACL
    2009
    130views Computational Linguistics» more  ACL 2009»
    Unsupervised Learning of Narrative Schemas and their Participants
    13 years 6 months ago
    Unsupervised Learning of Narrative Schemas and their Participants
    Download  cs.stanford.edu
    We describe an unsupervised system for learning narrative schemas, coherent sequences or sets of events (arrested(POLICE,SUSPECT), convicted( JUDGE, SUSPECT)) whose arguments are ...
    Nathanael Chambers, Dan Jurafsky
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    ECCV
    2004
    Springer
    157views Computer Vision» more  ECCV 2004»
    A Statistical Model for General Contextual Object Recognition
    14 years 11 months ago
    A Statistical Model for General Contextual Object Recognition
    Download  people.cs.ubc.ca
    We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
    Peter Carbonetto, Nando de Freitas, Kobus Barnard
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