Online prediction methods are typically presented as serial algorithms running on a single processor. However, in the age of web-scale prediction problems, it is increasingly comm...
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin X...
Actor-Critic based approaches were among the first to address reinforcement learning in a general setting. Recently, these algorithms have gained renewed interest due to their gen...
Abstract— Today’s embedded systems are typically distributed and more often confronted with timevarying demands. Existing methodologies that optimize the partitioning of comput...
— We explore an online problem where a group of robots has to find a target whose position is unknown in an unknown planar environment whose geometry is acquired by the robots d...
For discrete-time linear time invariant systems with constraints on inputs and states, we develop an algorithm to determine explicitly, the state feedback control law which minimi...
Alberto Bemporad, Manfred Morari, Vivek Dua, Efstr...