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    NIPS
    1998
    112views Information Technology» more  NIPS 1998»
    Learning from Dyadic Data
    13 years 9 months ago
    Learning from Dyadic Data
    Download  www.cs.berkeley.edu
    Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
    Thomas Hofmann, Jan Puzicha, Michael I. Jordan
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    CDES
    2009
    87views Hardware» more  CDES 2009»
    Delay-Insensitive Ternary Logic
    13 years 8 months ago
    Delay-Insensitive Ternary Logic
    Download  comp.uark.edu
    This paper develops a delay-insensitive (DI) digital design paradigm that utilizes ternary logic as an alternative to dual-rail logic for encoding the DATA and NULL states. This ne...
    Ravi Sankar Parameswaran Nair, Scott C. Smith, Jia...
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    CASCON
    1993
    117views Education» more  CASCON 1993»
    Documenting-in-the-large vs. documenting-in-the-small
    13 years 9 months ago
    Documenting-in-the-large vs. documenting-in-the-small
    Download  rigi.cs.uvic.ca
    There is a signi cant di erence between documentinglarge programs and documenting small ones. By large programs we mean on the order of 1,000,000 lines, usually written by many di...
    Scott R. Tilley
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    BNCOD
    1997
    111views Database» more  BNCOD 1997»
    Improved and Optimized Partitioning Techniques in Database Query Processing
    13 years 9 months ago
    Improved and Optimized Partitioning Techniques in Database Query Processing
    Download  www.idi.ntnu.no
    Abstract. In this paper we present two improvements to the partitioning process: 1) A new dynamic bu er management strategy is employed to increase the average block size of I/O-tr...
    Kjell Bratbergsengen, Kjetil Nørvåg
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    ESANN
    1998
    170views Neural Networks» more  ESANN 1998»
    Recurrent SOM with local linear models in time series prediction
    13 years 9 months ago
    Recurrent SOM with local linear models in time series prediction
    Download  www.dice.ucl.ac.be
    Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
    Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...
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