We propose Merge Growing Neural Gas (MGNG) as a novel unsupervised growing neural network for time series analysis. MGNG combines the state-of-the-art recursive temporal context of...
Andreas Andreakis, Nicolai von Hoyningen-Huene, Mi...
We investigate techniques for visualizing time series data and evaluate their effect in value comparison tasks. We compare line charts with horizon graphs--a space-efficient time ...
Discrete stochastic models (DSM) are widely used in various application fields today. Proxel-based simulation can outperform discrete event-based approaches in the analysis of smal...
We consider the problem of representing, in a space-efficient way, a function f : S → Σ such that any function value can be computed in constant time on a RAM. Specifically, ou...
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...