In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
We consider the online problem of scheduling jobs with equal processing times on a single machine. Each job has a release time and a deadline, and the goal is to maximize the numb...
Online learned tracking is widely used for it’s adaptive ability to handle appearance changes. However, it introduces potential drifting problems due to the accumulation of erro...
This paper considers online stochastic optimization problems where uncertainties are characterized by a distribution that can be sampled and where time constraints severely limit t...
— We put forth a unified framework for downlink and uplink scheduling of multiple connections with diverse qualityof-service requirements, where each connection transmits using ...