In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for t...
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
Feature subset selection presents a common challenge for the applications where data with tens or hundreds of features are available. Existing feature selection algorithms are mai...
The Poisson-Boltzmann equation is an important tool in modeling solvent in biomolecular systems. In this paper, we focus on numerical approximations to the electrostatic potential...
Stephen D. Bond, Jehanzeb Hameed Chaudhry, Eric C....
Some aspects of goal-oriented a posteriori error estimation are addressed in the context of steady convection-diffusion equations. The difference between the exact and approxima...