Classically, an approach to the multiagent policy learning supposed that the agents, via interactions and/or by using preliminary knowledge about the reward functions of all playe...
We present a learning-based, sliding window-style approach for the problem of detecting humans in still images. Instead of traditional concatenation-style image location-based feat...
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
We propose a measurement-based routing algorithm to load-balance intradomain traffic along multiple paths for multiple unicast sources. Multiple paths are established using overla...
The need for supporting CSCW applications with heterogeneous and varying user requirements call for adaptive and reconfigurable schedulers accommodating a mixture of real-time, pro...