Usually time series prediction is done with regularly sampled data. In practice, however, the data available may be irregularly sampled. In this case the conventional prediction me...
We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
— In this paper, we propose the use of QoS routing to enhance the support of IP Telephony. Our proposed scheme is based on QoS intradomain OSPF routing, an extension of the conve...
Alex Dubrovsky, Mario Gerla, Scott Seongwook Lee, ...
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...
Prediction of time series is an important problem in many areas of science and engineering. Extending the horizon of predictions further to the future is the challenging and diffic...