A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
[HTML][HTML] Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges
The current expansion of theory and research on artificial intelligence in management and
organization studies has revitalized the theory and research on decision-making in …
organization studies has revitalized the theory and research on decision-making in …
Making disk failure predictions {SMARTer}!
Disk drives are one of the most commonly replaced hardware components and continue to
pose challenges for accurate failure prediction. In this work, we present analysis and …
pose challenges for accurate failure prediction. In this work, we present analysis and …
Taming performance variability
The performance of compute hardware varies: software run repeatedly on the same server
(or a different server with supposedly identical parts) can produce performance results that …
(or a different server with supposedly identical parts) can produce performance results that …
Hyrax:{Fail-in-Place} Server Operation in Cloud Platforms
Today's cloud platforms handle server hardware failures by shutting down the affected
server and only turning it back online once it has been repaired by a technician. At cloud …
server and only turning it back online once it has been repaired by a technician. At cloud …
System-level hardware failure prediction using deep learning
Disk and memory faults are the leading causes of server breakdown. A proactive solution is
to predict such hardware failure at the runtime and then isolate the hardware at risk and …
to predict such hardware failure at the runtime and then isolate the hardware at risk and …
[HTML][HTML] Anomaly-based error and intrusion detection in tabular data: No DNN outperforms tree-based classifiers
Recent years have seen a growing involvement of researchers and practitioners in crafting
Deep Neural Networks (DNNs) that seem to outperform existing machine learning …
Deep Neural Networks (DNNs) that seem to outperform existing machine learning …
Dependability and security quantification of an internet of medical things infrastructure based on cloud-fog-edge continuum for healthcare monitoring using …
TA Nguyen, D Min, E Choi… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Rising aggressive virus pandemics urge to conduct studies on dependability and security of
modern computing systems to secure autonomous and continuous operations of healthcare …
modern computing systems to secure autonomous and continuous operations of healthcare …
Dram failure prediction in aiops: Empirical evaluation, challenges and opportunities
DRAM failure prediction is a vital task in AIOps, which is crucial to maintain the reliability and
sustainable service of large-scale data centers. However, limited work has been done on …
sustainable service of large-scale data centers. However, limited work has been done on …
SmartOClock: Workload-and risk-aware overclocking in the cloud
Operating server components beyond their voltage and power design limit (ie, overclocking)
enables improving performance and lowering cost for cloud workloads. However …
enables improving performance and lowering cost for cloud workloads. However …