: Recurrent neural networks possess interesting universal approximation capabilities, making them good candidates for time series modeling. Unfortunately, long term dependencies ar...
In building practical sensor networks, it is often beneficial to use only a subset of sensors to take measurements because of computational, communication, and power limitations....
Yoonheui Kim, Victor R. Lesser, Deepak Ganesan, Ra...
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominat...
Abstract—This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discu...
This paper considers the problem of an agent searching for a resource or a tangible good in a physical environment, where at each stage of its search it observes one source where ...
Yonatan Aumann, Noam Hazon, Sarit Kraus, David Sar...