This paper surveys the machine learning literature and presents in an optimization
framework several commonly used machine learning approaches. Particularly …

The eukaryotic cell is compartmentalized into subcellular niches, including membrane-
bound and membrane-less organelles. Proteins localize to these niches to fulfil their …

The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …

The fastcluster package is a C++ library for hierarchical, agglomerative clustering. It provides
a fast implementation of the most efficient, current algorithms when the input is a dissimilarity …

Social networks have become an indispensable activity in people's lives. A number of
previous studies have investigated various social networks and probed in the core …

This paper presents algorithms for hierarchical, agglomerative clustering which perform
most efficiently in the general-purpose setup that is given in modern standard software …

Data analysis plays an indispensable role for understanding various phenomena. Cluster
analysis, primitive exploration with little or no prior knowledge, consists of research …

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 …

NP-hardness of Euclidean sum-of-squares clustering Page 1 Mach Learn (2009) 75: 245–248
DOI 10.1007/s10994-009-5103-0 NP-hardness of Euclidean sum-of-squares clustering Daniel …

This is the first book to take a truly comprehensive look at clustering. It begins with an
introduction to cluster analysis and goes on to explore: proximity measures; hierarchical …