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JITECH
2010
106views more  JITECH 2010»
15 years 1 months ago
Patterns and structures of intra-organizational learning networks within a knowledge-intensive organization
This paper employs the network perspective to study patterns and structures of intraorganizational learning networks. The theoretical background draws from cognitive theories, the...
Miha Skerlavaj, Vlado Dimovski, Kevin C. Desouza
126
Voted
BMCBI
2006
239views more  BMCBI 2006»
15 years 2 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
131
Voted
ICANN
2010
Springer
15 years 2 months ago
Tumble Tree - Reducing Complexity of the Growing Cells Approach
We propose a data structure that decreases complexity of unsupervised competitive learning algorithms which are based on the growing cells structures approach. The idea is based on...
Hendrik Annuth, Christian-A. Bohn
132
Voted
ISMB
1993
15 years 4 months ago
Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools
Weintroduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECTis able to ra...
Kevin J. Cherkauer, Jude W. Shavlik
177
Voted
IDA
2005
Springer
15 years 8 months ago
Combining Bayesian Networks with Higher-Order Data Representations
Abstract. This paper introduces Higher-Order Bayesian Networks, a probabilistic reasoning formalism which combines the efficient reasoning mechanisms of Bayesian Networks with the...
Elias Gyftodimos, Peter A. Flach