Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
Creating video recordings of events such as lectures or meetings is increasingly inexpensive and easy. However, reviewing the content of such video may be time-consuming and difï¬...
Modeling text with topics is currently a popular research area in both Machine Learning and Information Retrieval (IR). Most of this research has focused on automatic methods thou...
In database query processing, actual run-time conditions (e.g., actual selectivities and actual available memory) very often differ from compile-time expectations of run-time cond...