We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
The purpose of this paper is to describe (a) why simulation is necessary to evaluate check-in, (b) a simulation toolbox for check-in counters and (c) Two case studies for Amsterda...
Collaboration between peers is an important aspect of the learning process and can considerably augment learning in studying complex domains. To ensure that peer collaboration occ...
Wildfire propagation is a complex process influenced by many factors. Simulation models of wildfire spread, such as DEVS-FIRE, are important tools for studying fire behavior. This...