High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …

This is Part II of the two-part comprehensive survey devoted to a computing framework most
commonly known under the names Hyperdimensional Computing and Vector Symbolic …

In massive and rapid graph streams, a useful and important task is to summarize the
structure of graph streams in order to enable efficient and effective graph query processing …

When network is undergoing problems such as congestion, scan attack, DDoS attack, etc.,
measurements are much more important than usual. In this case, traffic characteristics …

We present NetCache, a new key-value store architecture that leverages the power and
flexibility of new-generation programmable switches to handle queries on hot items and …

Count-based exploration algorithms are known to perform near-optimally when used in
conjunction with tabular reinforcement learning (RL) methods for solving small discrete …

Incremental learning, online learning, and data stream learning are terms commonly
associated with learning algorithms that update their models given a continuous influx of …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Traditionally, the data plane has been designed with fixed functions to forward packets using
a small set of protocols. This closed-design paradigm has limited the capability of the …

Massive and dynamic networks arise in many practical applications such as social media,
security and public health. Given an evolutionary network, it is crucial to detect structural …