We propose a neuro-genetic daily stock prediction model. Traditional indicators of stock prediction are utilized to produce useful input features of neural networks. The genetic al...
In sequential prediction tasks, one repeatedly tries to predict the next element in a sequence. A classical way to solve these problems is to fit an order-n Markov model to the da...
Interactive multimedia sessions have uncertain, varying consumption rates due to users' interactive behavior. In this paper, we propose two approaches for prediction of consu...
In high-performance computer systems, performance losses due to conditional branch instructions can be minimized by predicting a branch outcome and fetching, decoding, and/or issu...
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...