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» Toward network data independence
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JMLR
2006
169views more  JMLR 2006»
15 years 4 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
146
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DIS
2009
Springer
15 years 11 months ago
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Annalisa Appice, Michelangelo Ceci, Donato Malerba
INFOCOM
2006
IEEE
15 years 10 months ago
Predictability of WLAN Mobility and Its Effects on Bandwidth Provisioning
— Wireless local area networks (WLANs) are emerging as a popular technology for access to the Internet and enterprise networks. In the long term, the success of WLANs depends on ...
Libo Song, Udayan Deshpande, Ulas C. Kozat, David ...
CIKM
2008
Springer
15 years 6 months ago
Classifying networked entities with modularity kernels
Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
Dell Zhang, Robert Mao
IJAR
2010
130views more  IJAR 2010»
15 years 3 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki