Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
We present a robust vision system for single person tracking inside a smart room using multiple synchronized, calibrated, stationary cameras. The system consists of two main compo...
ZhenQiu Zhang, Gerasimos Potamianos, Stephen M. Ch...
Real-world face recognition systems often have to face the single sample per person (SSPP) problem, that is, only a single training sample for each person is enrolled in the datab...
Abstract. We give a lower bound for the error of any unitarily invariant algorithm learning half-spaces against the uniform or related distributions on the unit sphere. The bound i...
System performance in multi-agent resource allocation systems can often improve if individual agents reduce their activity. Agents in such systems need a way to modulate their ind...
H. Van Dyke Parunak, Sven Brueckner, Robert S. Mat...