In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
Multiobjective methods are ideal for evolving a set of portfolio optimisation solutions that span a range from highreturn/high-risk to low-return/low-risk, and an investor can cho...
Dynamic time-linkage problems (DTPs) are common types of dynamic optimization problems where "decisions that are made now ... may in‡uence the maximum score that can be obta...
In clique tree clustering, inference consists of propagation in a clique tree compiled from a Bayesian network. In this paper, we develop an analytical approach to characterizing ...