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» The structure of intrinsic complexity of learning
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BMCBI
2010
160views more  BMCBI 2010»
13 years 7 months ago
Identification of functional hubs and modules by converting interactome networks into hierarchical ordering of proteins
Background: Protein-protein interactions play a key role in biological processes of proteins within a cell. Recent high-throughput techniques have generated protein-protein intera...
Young-Rae Cho, Aidong Zhang
CSREAEEE
2008
79views Business» more  CSREAEEE 2008»
13 years 9 months ago
Implementing Standard Reference Models for e-learning Systems
- Active development in the field of e-Learning has led to multiple organizations and specifications that try to provide some interoperability to systems, tools and learning conten...
Juan-Manuel de Blas, Luis de Marcos, Roberto Barch...
LAMAS
2005
Springer
14 years 1 months ago
Multi-agent Relational Reinforcement Learning
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
COGSCI
2008
139views more  COGSCI 2008»
13 years 7 months ago
A Computational Model of Early Argument Structure Acquisition
How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in ...
Afra Alishahi, Suzanne Stevenson
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali