Tracking the identities of moving objects is an important aspect of most multi-object tracking applications. Uncertainty in sensor data, coupled with the intrinsic difficulty of ...
Jaewon Shin, Nelson Lee, Sebastian Thrun, Leonidas...
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
The most important and interesting of the computing challenges we are facing are those that involve the problems and opportunities afforded by massive decentralization and disinte...
In this paper we extend the PAC learning algorithm due to Clark and Thollard for learning distributions generated by PDFA to automata whose transitions may take varying time length...