CAFE: Adaptive VDI Workload Prediction with Multi-Grained Features
نویسندگان
چکیده
منابع مشابه
Workload Adaptive Power Management with Live Phase Monitoring and Prediction
In current computer systems, power dissipation is widely recognized as one of the primary critical constraints. Improving the power efficiency of current and emerging systems has therefore become a pressing challenge and an active research area over recent years. Dynamic, on-the-fly management techniques aim to address this challenge by adaptively responding to the changes in application execut...
متن کاملFine-Grained Classification of Named Entities by Fusing Multi-Features
Due to the increase in the number of classes and the decrease in the semantic differences between classes, fine-grained classification of Named Entities is a more difficult task than classic classification of NEs. Using only simple local context features for this fine-grained task cannot yield a good classification performance. This paper proposes a method exploiting Multi-features for fine-gra...
متن کاملMulti-features taxi destination prediction with frequency domain processing
The traditional taxi prediction methods model the taxi trajectory as a sequence of spatial points. It cannot represent two-dimensional spatial relationships between trajectory points. Therefore, many methods transform the taxi GPS trajectory into a two-dimensional image, and express the spatial correlations by trajectory image. However, the trajectory image may have noise and sparsity according...
متن کاملFine-Grained Sentiment Analysis with Structural Features
Sentiment analysis is the problem of determining the polarity of a text with respect to a particular topic. For most applications, however, it is not only necessary to derive the polarity of a text as a whole but also to extract negative and positive utterances on a more finegrained level. Sentiment analysis systems working on the (sub-)sentence level, however, are difficult to develop since sh...
متن کاملImproving Dependency Parsing with Fined-Grained Features
In this paper, we present a simple and effective fine-grained feature generation scheme for dependency parsing. We focus on the problem of grammar representation, introducing fine-grained features by splitting various POS tags to different degrees using HowNet hierarchical semantic knowledge. To prevent the oversplitting, we adopt a threshold-constrained bottomup strategy to merge the derived s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the AAAI Conference on Artificial Intelligence
سال: 2019
ISSN: 2374-3468,2159-5399
DOI: 10.1609/aaai.v33i01.33015821