Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
Many mathematical models have been proposed to evaluate the execution performance of an application with and without checkpointing in the presence of failures. They assume that th...
Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...
Prior research into search system scalability has primarily addressed query processing efficiency [1, 2, 3] or indexing efficiency [3], or has presented some arbitrary system arch...
This paper addresses the issue of optimal scale selection for circular edge extraction in the context of higher dimensional multiscale edge extraction. Based on a classification o...