Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
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...
Feature selection for unsupervised tasks is particularly challenging, especially when dealing with text data. The increase in online documents and email communication creates a nee...
Nirmalie Wiratunga, Robert Lothian, Stewart Massie
This paper presents a hybrid technique that combines List Scheduling (LS) with Genetic Algorithms (GA) for constructing non-preemptive schedules for soft real-time parallel applic...
Flexible user interfaces that can be customized to meet the needs of the task at hand are particularly important for real-time group collaboration. This paper presents the user in...