Traditional indexing techniques are not well suited for complex data types such as spatial, spatio-temporal, and multimedia data types, where an instance is a composite of multipl...
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the req...
Abstract. Wireless sensor networks are often densely deployed for environmental monitoring applications. Collecting raw data from these networks can lead to excessive energy consum...
Supriyo Chatterjea, Tim Nieberg, Yang Zhang, Paul ...
We consider the problem of detecting anomalies in high arity categorical datasets. In most applications, anomalies are defined as data points that are 'abnormal'. Quite ...