An important goal of the theory of genetic algorithms is to build predictive models of how well genetic algorithms are expected to perform, given a representation, a fitness lands...
The implementation of Bayesian predictive procedures under standard normal models is considered. Two distributions are of particular interest, the K-prime and Ksquare distribution...
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...
We propose a model for describing the parallel performance of multigrid software on distributed memory architectures. The goal of the model is to allow reliable predictions to be m...
Abstract— We propose a new delay-constrained minimumhop distributed routing algorithm (DCMH) for unicastrouting. DCMH uses a novel path feasibility prediction (PFP) model that is...