In this paper, we devise a method for the estimation of the true support of itemsets on data streams, with the objective to maximize one chosen criterion among {precision, recall}...
Pierre-Alain Laur, Richard Nock, Jean-Emile Sympho...
In recent years manifold methods have attracted a considerable amount of attention in machine learning. However most algorithms in that class may be termed “manifold-motivatedâ€...
A general model is proposed for studying ranking problems. We investigate learning methods based on empirical minimization of the natural estimates of the ranking risk. The empiric...
A class of synchronization protocols for dense, large-scale sensor networks is presented. The protocols build on the recent work of Hong, Cheow, and Scaglione [5, 6] in which the ...
Abstract. This paper studies the inducement of sequentiality in genetic algorithms (GAs) for uniformly-scaled problems. Sequentiality is a phenomenon in which sub-solutions converg...
Kei Ohnishi, Kumara Sastry, Ying-Ping Chen, David ...