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KDD
2004
ACM
139views Data Mining» more  KDD 2004»
15 years 10 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
15 years 3 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
BERTINORO
2005
Springer
15 years 3 months ago
Emergent Consensus in Decentralised Systems Using Collaborative Reinforcement Learning
Abstract. This paper describes the application of a decentralised coordination algorithm, called Collaborative Reinforcement Learning (CRL), to two different distributed system pr...
Jim Dowling, Raymond Cunningham, Anthony Harringto...
BROADNETS
2004
IEEE
15 years 1 months ago
Efficient QoS Provisioning for Adaptive Multimedia in Mobile Communication Networks by Reinforcement Learning
The scarcity and large fluctuations of link bandwidth in wireless networks have motivated the development of adaptive multimedia services in mobile communication networks, where i...
Fei Yu, Vincent W. S. Wong, Victor C. M. Leung
HPDC
2010
IEEE
14 years 11 months ago
Lessons learned from moving earth system grid data sets over a 20 Gbps wide-area network
In preparation for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report, the climate community will run the Coupled Model Intercomparison Project phase 5 (...
Rajkumar Kettimuthu, Alex Sim, Dan Gunter, Bill Al...