Noscope: optimizing neural network queries over video at scale
Recent advances in computer vision-in the form of deep neural networks-have made it
possible to query increasing volumes of video data with high accuracy. However, neural …
possible to query increasing volumes of video data with high accuracy. However, neural …
How do users like this feature? a fine grained sentiment analysis of app reviews
App stores allow users to submit feedback for downloaded apps in form of star ratings and
text reviews. Recent studies analyzed this feedback and found that it includes information …
text reviews. Recent studies analyzed this feedback and found that it includes information …
{PRETZEL}: Opening the black box of machine learning prediction serving systems
Machine Learning models are often composed of pipelines of transformations. While this
design allows to efficiently execute single model components at training time, prediction …
design allows to efficiently execute single model components at training time, prediction …
Adaptive stream resource management using kalman filters
To answer user queries efficiently, a stream management system must handle continuous,
high-volume, possibly noisy, and time-varying data streams. One major research area in …
high-volume, possibly noisy, and time-varying data streams. One major research area in …
{EdgeWise}: A better stream processing engine for the edge
Many Internet of Things (IoT) applications would benefit if streams of data could be analyzed
rapidly at the Edge, near the data source. However, existing Stream Processing Engines …
rapidly at the Edge, near the data source. However, existing Stream Processing Engines …
[كتاب][B] Stream data processing: a quality of service perspective: modeling, scheduling, load shedding, and complex event processing
S Chakravarthy, Q Jiang - 2009 - books.google.com
In recent years, a new class of applications has come to the forefront {p-marily due to the
advancement in our ability to collect data from multitudes of devices, and process them e …
advancement in our ability to collect data from multitudes of devices, and process them e …
DRS: Dynamic resource scheduling for real-time analytics over fast streams
In a data stream management system (DSMS), users register continuous queries, and
receive result updates as data arrive and expire. We focus on applications with real-time …
receive result updates as data arrive and expire. We focus on applications with real-time …
Optimal sampling from sliding windows
A sliding windows model is an important case of the streaming model, where only the most"
recent" elements remain active and the rest are discarded in a stream. The sliding windows …
recent" elements remain active and the rest are discarded in a stream. The sliding windows …
DRS: Auto-scaling for real-time stream analytics
In a stream data analytics system, input data arrive continuously and trigger the processing
and updating of analytics results. We focus on applications with real-time constraints, in …
and updating of analytics results. We focus on applications with real-time constraints, in …
[PDF][PDF] Real-Time Analytics In Streaming Big Data: Techniques And Applications
The rise of streaming big data has revolutionized the domain of real-time analytics, enabling
organizations to process and analyze data as it is generated (Sun et al., 2020). Unlike …
organizations to process and analyze data as it is generated (Sun et al., 2020). Unlike …