This paper is about the evolutionary design of multi-agent systems. An important part of recent research in this domain has been focusing on collaborative revolutionary methods. W...
Multi-view learners reduce the need for labeled data by exploiting disjoint sub-sets of features (views), each of which is sufficient for learning. Such algorithms assume that eac...
Recent work in data integration has shown the importance of statistical information about the coverage and overlap of data sources for efficient query processing. Gathering and s...
In this paper, we evaluate the use of implicit interest indicators as the basis for user profiling in the Digital TV domain. Research in more traditional domains, such as Web brow...
This paper presents a novel, promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parity functions. Lookahead is the st...