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Reducing Monitoring Overhead in Virtualized Environments Through Feature Selection.

, , and . SBRC, page 15-28. (2018)

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A framework for virtual screening., , , , , and . SAC, page 31-36. ACM, (2016)Inference of regulatory networks with a convergence improved MCMC sampler., , and . BMC Bioinform., (2015)An MCDM Approach to the Selection of Novel Technologies for Innovative In-Vehicle Information Systems., , , , , , , and . IJDSST, 8 (1): 43-55 (2016)Mining flexible-receptor molecular docking data., , , and . WIREs Data Mining Knowl. Discov., 1 (6): 532-541 (2011)A Study on the Relationship between Internal and External Validity Indices Applied to Partitioning and Density-based Clustering Algorithms., , , and . ICEIS (1), page 89-98. SciTePress, (2017)Association Rules to Identify Receptor and Ligand Structures through Named Entities Recognition., , , and . IEA/AIE (3), volume 6098 of Lecture Notes in Computer Science, page 119-128. Springer, (2010)Reducing Monitoring Overhead in Virtualized Environments Through Feature Selection., , and . SBRC, page 15-28. (2018)Deduplicação de Contatos em Dispositivos Móveis Utilizando Similaridade Textual e Aprendizado de Máquina Contacts Deduplication in Mobile Devices Using Textual Similarity and Machine Learning., , , and . SBSI, page 160-167. ACM, (2016)Extracting Information from Flexible Receptor-Flexible Ligand Docking Experiments., , , , and . BSB, volume 5167 of Lecture Notes in Computer Science, page 104-114. Springer, (2008)FReDD: Supporting Mining Strategies through a Flexible-Receptor Docking Database., , , and . BSB, volume 5676 of Lecture Notes in Computer Science, page 143-146. Springer, (2009)