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» Theoretical Frameworks for Data Mining
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SDM
2008
SIAM
144views Data Mining» more  SDM 2008»
15 years 6 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»
15 years 4 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»
13 years 7 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»
15 years 4 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
16 years 4 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