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A survey on distributed machine learning
The demand for artificial intelligence has grown significantly over the past decade, and this
growth has been fueled by advances in machine learning techniques and the ability to …
growth has been fueled by advances in machine learning techniques and the ability to …
Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions
The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …
lives, including environmental pollution, public security, road congestion, etc. New …
Digital twin: Values, challenges and enablers from a modeling perspective
Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
Edge intelligence: Empowering intelligence to the edge of network
Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …
caching, processing, and analysis proximity to where data are captured based on artificial …
The four dimensions of social network analysis: An overview of research methods, applications, and software tools
Social network based applications have experienced exponential growth in recent years.
One of the reasons for this rise is that this application domain offers a particularly fertile …
One of the reasons for this rise is that this application domain offers a particularly fertile …
Machine learning with big data: Challenges and approaches
The Big Data revolution promises to transform how we live, work, and think by enabling
process optimization, empowering insight discovery and improving decision making. The …
process optimization, empowering insight discovery and improving decision making. The …
Big IoT data analytics: architecture, opportunities, and open research challenges
Voluminous amounts of data have been produced, since the past decade as the
miniaturization of Internet of things (IoT) devices increases. However, such data are not …
miniaturization of Internet of things (IoT) devices increases. However, such data are not …
Machine learning on big data: Opportunities and challenges
Abstract Machine learning (ML) is continuously unleashing its power in a wide range of
applications. It has been pushed to the forefront in recent years partly owing to the advent of …
applications. It has been pushed to the forefront in recent years partly owing to the advent of …
A survey of data partitioning and sampling methods to support big data analysis
Computer clusters with the shared-nothing architecture are the major computing platforms
for big data processing and analysis. In cluster computing, data partitioning and sampling …
for big data processing and analysis. In cluster computing, data partitioning and sampling …
Big Data in the construction industry: A review of present status, opportunities, and future trends
The ability to process large amounts of data and to extract useful insights from data has
revolutionised society. This phenomenon—dubbed as Big Data—has applications for a wide …
revolutionised society. This phenomenon—dubbed as Big Data—has applications for a wide …