There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution for a variable rather than simply the most lik...
Michael Carney, Padraig Cunningham, Jim Dowling, C...
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,...
Distributed stream processing systems (DSPSs) have many important applications such as sensor data analysis, network security, and business intelligence. Failure management is ess...
Xiaohui Gu, Spiros Papadimitriou, Philip S. Yu, Sh...
This study investigates how specification of return distribution for REIT influences the performance of volatility forecasting using three GARCH models (GARCH-N, GARCH-ST and GARC...