This paper proposes and experimentally assesses a machine learning approach for supporting the effective and efficient generation of synthetic memory reference traces for a wide range of application scenarios. The proposed approach makes a nice use of extended hierarchical Markov models
An Effective and Efficient Approach for Supporting the Generation of Synthetic Memory Reference Traces via Hierarchical Hidden/Non-Hidden Markov Models
Alfredo Cuzzocrea;
2018-01-01
Abstract
This paper proposes and experimentally assesses a machine learning approach for supporting the effective and efficient generation of synthetic memory reference traces for a wide range of application scenarios. The proposed approach makes a nice use of extended hierarchical Markov modelsFile in questo prodotto:
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