Adapting Hidden Markov Models for Online Learning
نویسندگان
چکیده
منابع مشابه
Adapting Hidden Markov Models for Online Learning
In modern computer systems, the intermittent behaviour of infrequent, additional loads affects performance. Often, representative traces of storage disks or remote servers can be scarce and obtaining real data is sometimes expensive. Therefore, stochastic models, through simulation and profiling, provide cheaper, effective solutions, where input model parameters are obtained. A typical example ...
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ژورنال
عنوان ژورنال: Electronic Notes in Theoretical Computer Science
سال: 2015
ISSN: 1571-0661
DOI: 10.1016/j.entcs.2015.10.022