The main purpose of data mining and analytics is to find novel, potentially useful patterns
that can be utilized in real-world applications to derive beneficial knowledge. For identifying …

Under several emerging application scenarios, such as in smart cities, operational
monitoring of large infrastructure, wearable assistance, and Internet of Things, continuous …

Class-incremental learning (CIL) aims to adapt to emerging new classes without forgetting
old ones. Traditional CIL models are trained from scratch to continually acquire knowledge …

The ability to learn new concepts continually is necessary in this ever-changing world.
However, deep neural networks suffer from catastrophic forgetting when learning new …

A model is an artefact to represent a specific concept. It maps properties of the concept into
some abstract representation, driven by the purpose of the model. As such, models …

In almost every scientific field, measurements are performed over time. These observations
lead to a collection of organized data called time series. The purpose of time-series data …

Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …

With the ubiquity of real-time data, organizations need streaming systems that are scalable,
easy to use, and easy to integrate into business applications. Structured Streaming is a new …

A large number of distributed applications requires continuous and timely processing of
information as it flows from the periphery to the center of the system. Examples include …

Many network solutions and overlay networks utilize probabilistic techniques to reduce
information processing and networking costs. This survey article presents a number of …