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    NIPS
    2008
    211views Information Technology» more  NIPS 2008»
    Multi-Level Active Prediction of Useful Image Annotations for Recognition
    13 years 11 months ago
    Multi-Level Active Prediction of Useful Image Annotations for Recognition
    Download  www.cs.utexas.edu
    We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...
    Sudheendra Vijayanarasimhan, Kristen Grauman
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    NIPS
    2008
    94views Information Technology» more  NIPS 2008»
    Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing
    13 years 11 months ago
    Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing
    Download  www.kyb.tuebingen.mpg.de
    EEG connectivity measures could provide a new type of feature space for inferring a subject's intention in Brain-Computer Interfaces (BCIs). However, very little is known on ...
    Moritz Grosse-Wentrup
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    NIPS
    2008
    143views Information Technology» more  NIPS 2008»
    An Online Algorithm for Maximizing Submodular Functions
    13 years 11 months ago
    An Online Algorithm for Maximizing Submodular Functions
    Download  www.cs.cmu.edu
    We present an algorithm for solving a broad class of online resource allocation . Our online algorithm can be applied in environments where abstract jobs arrive one at a time, and...
    Matthew J. Streeter, Daniel Golovin
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    NIPS
    2008
    166views Information Technology» more  NIPS 2008»
    Asynchronous Distributed Learning of Topic Models
    13 years 11 months ago
    Asynchronous Distributed Learning of Topic Models
    Download  www.datalab.uci.edu
    Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
    Arthur Asuncion, Padhraic Smyth, Max Welling
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    NIPS
    2008
    129views Information Technology» more  NIPS 2008»
    Structure Learning in Human Sequential Decision-Making
    13 years 11 months ago
    Structure Learning in Human Sequential Decision-Making
    Download  www-users.cs.umn.edu
    We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
    Daniel Acuña, Paul R. Schrater
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