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» Comparing the Bayes and Typicalness Frameworks
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CORR
2000
Springer
120views Education» more  CORR 2000»
13 years 7 months ago
Scaling Up Inductive Logic Programming by Learning from Interpretations
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
CCS
2011
ACM
12 years 7 months ago
BitShred: feature hashing malware for scalable triage and semantic analysis
The sheer volume of new malware found each day is growing at an exponential pace. This growth has created a need for automatic malware triage techniques that determine what malwar...
Jiyong Jang, David Brumley, Shobha Venkataraman
CVPR
2008
IEEE
14 years 9 months ago
Semi-supervised distance metric learning for Collaborative Image Retrieval
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, rele...
Steven C. H. Hoi, Wei Liu, Shih-Fu Chang
WWW
2007
ACM
14 years 8 months ago
Preference-based selection of highly configurable web services
A key challenge for dynamic Web service selection is that Web services are typically highly configurable and service requesters often have dynamic preferences on service configura...
Steffen Lamparter, Anupriya Ankolekar, Rudi Studer...
EDBT
2009
ACM
175views Database» more  EDBT 2009»
14 years 2 months ago
Towards materialized view selection for distributed databases
Materialized views (MV) can significantly improve the query performance of relational databases. In this paper, we consider MVs to optimize complex scenarios where many heterogen...
Leonardo Weiss Ferreira Chaves, Erik Buchmann, Fab...