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WIRN
2005
Springer
15 years 10 months ago
Recursive Neural Networks and Graphs: Dealing with Cycles
Recursive neural networks are a powerful tool for processing structured data. According to the recursive learning paradigm, the input information consists of directed positional ac...
Monica Bianchini, Marco Gori, Lorenzo Sarti, Franc...
SOSP
2003
ACM
16 years 1 months ago
Bullet: high bandwidth data dissemination using an overlay mesh
In recent years, overlay networks have become an effective alternative to IP multicast for efficient point to multipoint communication across the Internet. Typically, nodes self-...
Dejan Kostic, Adolfo Rodriguez, Jeannie R. Albrech...
BIBM
2008
IEEE
217views Bioinformatics» more  BIBM 2008»
15 years 11 months ago
Combining Hierarchical Inference in Ontologies with Heterogeneous Data Sources Improves Gene Function Prediction
The study of gene function is critical in various genomic and proteomic fields. Due to the availability of tremendous amounts of different types of protein data, integrating thes...
Xiaoyu Jiang, Naoki Nariai, Martin Steffen, Simon ...
AAAI
1990
15 years 6 months ago
Constructor: A System for the Induction of Probabilistic Models
The probabilistic network technology is a knowledgebased technique which focuses on reasoning under uncertainty. Because of its well defined semantics and solid theoretical founda...
Robert M. Fung, Stuart L. Crawford
JMLR
2010
134views more  JMLR 2010»
14 years 11 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...