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» Theoretical Frameworks for Data Mining
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SDM
2008
SIAM
144views Data Mining» more  SDM 2008»
13 years 10 months ago
Semi-supervised Multi-label Learning by Solving a Sylvester Equation
Multi-label learning refers to the problems where an instance can be assigned to more than one category. In this paper, we present a novel Semi-supervised algorithm for Multi-labe...
Gang Chen, Yangqiu Song, Fei Wang, Changshui Zhang
CORR
2000
Springer
120views Education» more  CORR 2000»
13 years 8 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 ...
KDD
2012
ACM
179views Data Mining» more  KDD 2012»
11 years 11 months ago
Transparent user models for personalization
Personalization is a ubiquitous phenomenon in our daily online experience. While such technology is critical for helping us combat the overload of information we face, in many cas...
Khalid El-Arini, Ulrich Paquet, Ralf Herbrich, Jur...
TITB
2008
204views more  TITB 2008»
13 years 8 months ago
A Cryptographic Approach to Securely Share and Query Genomic Sequences
To support large-scale biomedical research projects, organizations need to share person-specific genomic sequences without violating the privacy of their data subjects. In the past...
Murat Kantarcioglu, Wei Jiang, Ying Liu, Bradley M...
POPL
2004
ACM
14 years 9 months ago
Asynchronous and deterministic objects
We present in this article a precise security model for data confidentiality in the framework of asynchronous and deterministic objects. Our underlying programming model is based ...
Denis Caromel, Ludovic Henrio, Bernard P. Serpette