Traditionally, text classifiers are built from labeled training examples. Labeling is usually done manually by human experts (or the users), which is a labor intensive and time co...
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
e, the system labels constituents with either abstract semantic roles such as AGENT or PATIENT, or more domain-specific semantic roles such as SPEAKER, MESSAGE, and TOPIC. The syst...
In Multi-Objective Problems (MOPs) involving uncertainty, each solution might be associated with a cluster of performances in the objective space depending on the possible scenari...
This study proposes an agent-based model where adaptively learning agents with local vision who are situated in the Prisoner’s Dilemma game change their strategy and location as...