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» Learning and using relational theories
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ML
2012
ACM
413views Machine Learning» more  ML 2012»
12 years 5 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
JITECH
2010
116views more  JITECH 2010»
13 years 8 months ago
Design theory for dynamic complexity in information infrastructures: the case of building internet
We propose a design theory that tackles dynamic complexity in the design for Information Infrastructures (IIs) defined as a shared, open, heterogeneous and evolving socio-technica...
Ole Hanseth, Kalle Lyytinen
TIT
2002
97views more  TIT 2002»
13 years 9 months ago
On a relation between information inequalities and group theory
Abstract--In this paper, we establish a one-to-one correspondence between information inequalities and group inequalities. The major implication of our result is that we can prove ...
Terence H. Chan, Raymond W. Yeung
ATAL
2007
Springer
14 years 4 months ago
A framework for agent-based distributed machine learning and data mining
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek
WWW
2011
ACM
13 years 4 months ago
From actors, politicians, to CEOs: domain adaptation of relational extractors using a latent relational mapping
We propose a method to adapt an existing relation extraction system to extract new relation types with minimum supervision. Our proposed method comprises two stages: learning a lo...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...