The Pfair algorithms are optimal for independent periodic real-time tasks executing on a multiple-resource system, however, they incur a high scheduling overhead by making schedul...
We present a novel multi-object tracking algorithm based on multiple hypotheses about the trajectories of the objects. Our work is inspired by Reid's multiple hypothesis trac...
Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information, which originates from...
Smith Tsang, Ben Kao, Kevin Y. Yip, Wai-Shing Ho, ...
We study an approach for performing concurrent activities in Markov decision processes (MDPs) based on the coarticulation framework. We assume that the agent has multiple degrees ...
Decision-tree algorithms are known to be unstable: small variations in the training set can result in different trees and different predictions for the same validation examples. B...