A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...
As system integration evolves and tighter design constraints must be met, it becomes necessary to account for the non-ideal behavior of all the elements in a system. Certain devic...
Carlos P. Coelho, Joel R. Phillips, Luis Miguel Si...
— Recent advances in microelectronic technology have made it possible to construct compact and inexpensive wireless sensors. Sensor networks have received significant attention ...
We introduce the Multiplicative Update Selector and Estimator (MUSE) algorithm for sparse approximation in underdetermined linear regression problems. Given f = Φα∗ + µ, the ...
We consider the problem of maximizing a nonnegative (possibly non-monotone) submodular set function with or without constraints. Feige et al. [9] showed a 2/5-approximation for th...