A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
Due to the fast delivery of news articles by news providers on the Internet and/or via news datafeeds, it becomes an important research issue of predicting the risk of stocks by u...
Qi Pan, Hong Cheng, Di Wu, Jeffrey Xu Yu, Yiping K...
All discrete Fourier transform (DFT) domain-based speech enhancement gain functions rely on knowledge of the noise power spectral density (PSD). Since the noise PSD is unknown in a...
Richard C. Hendriks, Jesper Jensen, Richard Heusde...
Time series data is common in many settings including scientific and financial applications. In these applications, the amount of data is often very large. We seek to support pred...
Abstract. Approaches to data mining proposed so far are mainly symbolic decision trees and numerical feedforward neural networks methods. While decision trees give, in many cases, ...