Preserving digital information over the long term becomes increasing important for large number of institutions. The required expertise and limited tool support discourage especial...
Stephan Strodl, Petar Petrov, Michael Greifeneder,...
In this paper we propose a new probability update rule and sampling procedure for population-based incremental learning. These proposed methods are based on the concept of opposit...
Recent research on compact genetic algorithms (cGAs) has proposed a number of evolutionary search methods with reduced memory requirements. In cGAs, the evolution of populations is...
Alternating optimization algorithms for canonical polyadic decomposition (with/without nonnegative constraints) often accompany update rules with low computational cost, but could...
—This paper describes a new method to explore and discover within a large data set. We apply techniques from preference elicitation to automatically identify data elements that a...