In this paper, we propose an approach to estimate the Worst Case Response Time (WCRT) of tasks in a preemptive multi-tasking single-processor real-time system with a set associati...
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operate...
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. We approach this setting from a case-based perspective and propo...
We present new search algorithms to detect the occurrences of any pattern from a given pattern set in a text, allowing in the occurrences a limited number of spurious text charact...