The problem of subsampling in two-sample and K-sample settings is addressed where both the data and the statistics of interest take values in general spaces. We focus on the case ...
Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...
— The mining of meaningful shapes of time series is done widely in order to find shapes that can be used, for example, in classification problems or in summarizing signals. Nor...
Abstract. An overview of the Time Series Knowledge Mining framework to discover knowledge in multivariate time series is given. A hierarchy of temporal patterns, which are not a pr...