Using multilayer perceptrons (MLPs) to approximate the state-action value function in reinforcement learning (RL) algorithms could become a nightmare due to the constant possibilit...
We propose certified reduced basis methods for the efficient and reliable evaluation of a general output that is implicitly connected to a given parameterized input through the ha...
Yanlai Chen, Jan S. Hesthaven, Yvon Maday, Jer&oac...
abstractly; it is intended to provide a basis for implementing efficient and scalable parallel algorithms that correctly simulate DEVS models. Categories and Subject Descriptors: I...
Abstract We provide evidence that the unforgeability of several discrete-log based signatures like Schnorr signatures cannot be equivalent to the discrete log problem in the standa...
We treat feature selection and basis selection in a unified framework by introducing the masking matrix. If one considers feature selection as finding a binary mask vector that de...