Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
The problem of reinforcement learning in large factored Markov decision processes is explored. The Q-value of a state-action pair is approximated by the free energy of a product o...
The operation of six degree-of-freedom electromagnetic trackers is based on the spatial properties of the electromagnetic fields generated by three small coils. Anything in the e...
Mark A. Nixon, Bruce C. McCallum, W. Richard Frigh...
: The biomechanical properties of soft tissue derived from experimental measurements are critical for developing a reality-based model for minimally invasive surgical training and ...
Prior work in the eld of packet radio networks has often assumed a simple success-if-exclusive model of successful reception. This simple model is insucient to model interference...