Few-shot learning (FSL) has emerged as an effective learning method and shows great
potential. Despite the recent creative works in tackling FSL tasks, learning valid information …

Patient similarity networks (PSNs), where patients are represented as nodes and their
similarities as weighted edges, are being increasingly used in clinical research. These …

This chapter characterises the scope of this book. It explains the reasons why one should be
interested in cluster analysis, lists major application areas, basic theoretical and practical …

This volume contains the proceedings of the 7th Euro-China Conference on Intelligent Data
Analysis and Applications (ECC 2021), which is hosted by Communication University of …

The notion of graph which is most useful in computer science is that of a directed graph or
just a graph. A graph is a combinatorial structure consisting of a finite nonempty set of …

Starting with a new formulation for the mutual information (MI) between a pair of events, this
paper derives alternative upper bounds and extends those to the case of two discrete …

In machine learning, the presumably best model is selected from a variety of model
candidates generated by testing different model types, hyperparameters, or feature subsets …

The perceptual task of speech quality assessment (SQA) is a challenging task for machines
to do. Objective SQA methods that rely on the availability of the corresponding clean …

Previous functional connectivity studies have found both hypo‐and hyper‐connectivity in
brains of individuals having autism spectrum disorder (ASD). Here we studied abnormalities …

The increasing availability of large-scale protein-protein interaction data has made it
possible to understand the basic components and organization of cell machinery from the …