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    EACL
    2009
    ACL Anthology
    74views Natural Language Processing» more  EACL 2009»
    Improvements in Analogical Learning: Application to Translating Multi-Terms of the Medical Domain
    14 years 8 months ago
    Improvements in Analogical Learning: Application to Translating Multi-Terms of the Medical Domain
    Download  www.limsi.fr
    Handling terminology is an important matter in a translation workflow. However, current Machine Translation (MT) systems do not yet propose anything proactive upon tools which ass...
    François Yvon, Philippe Langlais, Pierre Zw...
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    DAGSTUHL
    2009
    144views Software Engineering» more  DAGSTUHL 2009»
    Statistical Mechanics of On-line Learning
    13 years 8 months ago
    Statistical Mechanics of On-line Learning
    Download  www.cs.rug.nl
    We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large...
    Michael Biehl, Nestor Caticha, Peter Riegler
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    ICALT
    2006
    IEEE
    106views Machine Learning» more  ICALT 2006»
    Mobile Learning: Is Anytime + Anywhere = Always Online?
    14 years 1 months ago
    Mobile Learning: Is Anytime + Anywhere = Always Online?
    Download  trifonova.net
    The new e-learning trend, called mobile learning opens variety of questions to solve. To allow access to learning content anytime and anyplace a technique called hoarding is somet...
    Anna Trifonova, Marco Ronchetti
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    JACIII
    2008
    101views more  JACIII 2008»
    On-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques
    13 years 7 months ago
    On-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques
    Download  www.ice.ci.ritsumei.ac.jp
    The development of on line model-based fault detection systems in machinery improves the operational reliability of industrial systems and reduces the operational and maintenance ...
    Chrissanthi Angeli, Avraam Chatzinikolaou
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    NIPS
    2004
    216views Information Technology» more  NIPS 2004»
    Using Machine Learning to Break Visual Human Interaction Proofs (HIPs)
    13 years 8 months ago
    Using Machine Learning to Break Visual Human Interaction Proofs (HIPs)
    Download  research.microsoft.com
    Machine learning is often used to automatically solve human tasks. In this paper, we look for tasks where machine learning algorithms are not as good as humans with the hope of ga...
    Kumar Chellapilla, Patrice Y. Simard
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