Many real-world domains bless us with a wealth of attributes to use for learning. This blessing is often a curse: most inductive methods generalize worse given too many attributes...
In recent years, there has been significant interest in development of ranking functions and efficient top-k retrieval algorithms to help users in ad-hoc search and retrieval in da...
Muhammed Miah, Gautam Das, Vagelis Hristidis, Heik...
Abstract. The maximum diversity problem (MDP) consists of identifying optimally diverse subsets of elements from some larger collection. The selection of elements is based on the d...
Geiza C. Silva, Luiz Satoru Ochi, Simone L. Martin...
Feature subset selection presents a common challenge for the applications where data with tens or hundreds of features are available. Existing feature selection algorithms are mai...
This paper studies the greedy ensemble selection family of algorithms for ensembles of regression models. These algorithms search for the globally best subset of regresmaking loca...
Ioannis Partalas, Grigorios Tsoumakas, Evaggelos V...