Cited By
View all- Berns FHuwel JBeecks C(2021)LOGIC: Probabilistic Machine Learning for Time Series Classification2021 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM51629.2021.00113(1000-1005)Online publication date: Dec-2021
We consider the problem of assigning an input vector to one of m classes by predicting P(c|${\schmi x}$) for c = 1, ..., m. For a two-class problem, the probability of class one given ${\schmi x}$ is estimated by (y(${\schmi x}$)), where (y) = 1/(1 + e ...
We investigate Gaussian Kullback-Leibler (G-KL) variational approximate inference techniques for Bayesian generalised linear models and various extensions. In particular we make the following novel contributions: sufficient conditions for which the G-KL ...
Time series are series of values ordered by time. This kind of data can be found in many real world settings. Classifying time series is a difficult task and an active area of research. This paper investigates the use of transfer learning in Deep ...
Association for Computing Machinery
New York, NY, United States
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inView or Download as a PDF file.
PDFView online with eReader.
eReaderView this article in HTML Format.
HTML Format