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The Effectiveness of Machine Learning to Estimate the Risk of Failure in Brazilian Public Contracts.

, , and . ICMLA, page 2071-2078. IEEE, (2023)

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Escalonamento justo em infraestruturas de nuvem com múltiplas classes de serviço., , , , , , and . SBRC, page 636-649. (2019)The Effectiveness of Machine Learning to Estimate the Risk of Failure in Brazilian Public Contracts., , and . ICMLA, page 2071-2078. IEEE, (2023)Functional verification methodology using Hierarchical Coloured Petri Nets-based testbenches., , , , , , and . SMC, page 2093-2098. IEEE, (2008)On the Efficiency Gains of Using Disaggregated Hardware to Build Warehouse-Scale Clusters., , , , , and . CloudCom, page 239-246. IEEE Computer Society, (2017)Supporting Mixed Workloads in OpenStack-Based Clouds., , , , , , , and . IEEE CLOUD, page 822-826. IEEE Computer Society, (2018)Instance Type Selection in Proactive Horizontal Auto-Scaling., , and . CloudCom, page 102-109. IEEE Computer Society, (2016)QoS-driven scheduling in the cloud., , , , , and . J. Internet Serv. Appl., 11 (1): 9 (2020)Autoflex: Service Agnostic Auto-scaling Framework for IaaS Deployment Models., , , , , and . CCGRID, page 42-49. IEEE Computer Society, (2013)