We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
Normal fuzzy CMAC neural network performs well because of its fast learning speed and local generalization capability for approximating nonlinear functions. However, it requires hu...
Floriberto Ortiz Rodriguez, Wen Yu, Marco A. Moren...
In this paper, we present a novel all-solutions preimage SAT solver, SOLALL, with the following features: (1) a new success-driven learning algorithm employing smaller cut sets; (...
This paper presents a study of the model of triple BAM by [11] which is an improved variation of the original BAM model by [7]. This class of model aims at integrating different s...
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...