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    ECSCW
    2003
    119views Software Engineering» more  ECSCW 2003»
    Informing the Development of Calendar Systems for Domestic Use
    13 years 9 months ago
    Informing the Development of Calendar Systems for Domestic Use
    Download  www.ecscw.org
    This paper contributes to the design of Groupware Calendar Systems (GCSs) for use in domestic life. We consider a number of ethnographic studies of calendar use in domestic circums...
    Andy Crabtree, Terry Hemmings, Tom Rodden, John A....
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    NIPS
    2001
    174views Information Technology» more  NIPS 2001»
    K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms
    13 years 9 months ago
    K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms
    Download  books.nips.cc
    Guided by an initial idea of building a complex (non linear) decision surface with maximal local margin in input space, we give a possible geometrical intuition as to why K-Neares...
    Pascal Vincent, Yoshua Bengio
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    SDM
    2004
    SIAM
    211views Data Mining» more  SDM 2004»
    Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
    13 years 9 months ago
    Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
    Download  www.dbs.informatik.uni-muenchen.de
    Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
    Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
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    TREC
    2004
    160views Information Technology» more  TREC 2004»
    Can We Get A Better Retrieval Function From Machine?
    13 years 9 months ago
    Can We Get A Better Retrieval Function From Machine?
    Download  trec.nist.gov
    The quality of an information retrieval system heavily depends on its retrieval function, which returns a similarity measurement between the query and each document in the collect...
    Weiguo Fan, Wensi Xi, Edward A. Fox, Li Wang
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    UAI
    2004
    141views Artificial Intelligence» more  UAI 2004»
    Recovering Articulated Object Models from 3D Range Data
    13 years 9 months ago
    Recovering Articulated Object Models from 3D Range Data
    Download  ai.stanford.edu
    We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to d...
    Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang,...
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