One reasonable categorization of coordination models is into data sharing or message passing, based on whether the information necessary to coordination is persistently stored and...
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
—This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high-resolution images based ...
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
This article investigates fundamental issues in scaling autonomous personal robots towards open-ended sets of everyday manipulation tasks which involve high complexity and vague j...