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JMLR
2002
138views more  JMLR 2002»
15 years 6 months ago
Learning Probabilistic Models of Link Structure
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin...
NIPS
2007
15 years 7 months ago
Learning the structure of manifolds using random projections
We present a simple variant of the k-d tree which automatically adapts to intrinsic low dimensional structure in data.
Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul ...
ICDM
2008
IEEE
127views Data Mining» more  ICDM 2008»
16 years 26 days ago
The Impact of Structural Changes on Predictions of Diffusion in Networks
In a typical realistic scenario, there exist some past data about the structure of the network which are analyzed with respect to some possibly future spreading process, such as b...
Mayank Lahiri, Arun S. Maiya, Rajmonda Sulo, Habib...
COR
2004
115views more  COR 2004»
15 years 6 months ago
Evaluation of decision trees: a multi-criteria approach
Data mining (DM) techniques are being increasingly used in many modern organizations to retrieve valuable knowledge structures from organizational databases, including data wareho...
Kweku-Muata Osei-Bryson
ER
2004
Springer
103views Database» more  ER 2004»
15 years 11 months ago
Modeling Default Induction with Conceptual Structures
Our goal is to model the way people induce knowledge from rare and sparse data. This paper describes a theoretical framework for inducing knowledge from these incomplete data descr...
Julien Velcin, Jean-Gabriel Ganascia