Discovering episodes, frequent sets of events from a sequence has been an active field in pattern mining. Traditionally, a level-wise approach is used to discover all frequent epis...
Given the pairwise affinity relations associated with a set of data items, the goal of a clustering algorithm is to automatically partition the data into a small number of homogen...
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...
Abstract. Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, usef...
Self-Organizing Maps (SOM) are very powerful tools for data mining, in particular for visualizing the distribution of the data in very highdimensional data sets. Moreover, the 2D m...