We explore the feasibility of muscle-computer interfaces (muCIs): an interaction methodology that directly senses and decodes human muscular activity rather than relying on physic...
T. Scott Saponas, Desney S. Tan, Dan Morris, Ravin...
In open systems where the components, i.e. the agents and the resources, may be unknown at design time, or in dynamic and self-organizing systems evolving with time, there is a ne...
Abstract—In order to harness the full compute power of manycore processors, future designs must focus on effective utilization of on-chip cache and bandwidth resources. In this p...
Hemayet Hossain, Sandhya Dwarkadas, Michael C. Hua...
—an interplay between mobile devices and static sensor nodes is envisioned in the near future. This will enable a heterogeneous design space that can offset the stringent resourc...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...