Deep Federated Anomaly Detection for Multivariate Time Series Data

no code implementations • 9 May 2022 • Wei Zhu, Dongjin Song, Yuncong Chen, Wei Cheng, Bo Zong, Takehiko Mizoguchi, Cristian Lumezanu, Haifeng Chen, Jiebo Luo

Specifically, we first design an Exemplar-based Deep Neural network (ExDNN) to learn local time series representations based on their compatibility with an exemplar module which consists of hidden parameters learned to capture varieties of normal patterns on each edge device.

Constrained Clustering Federated Learning +3

Ordinal-Quadruplet: Retrieval of Missing Classes in Ordinal Time Series

no code implementations • 24 Jan 2022 • Jurijs Nazarovs, Cristian Lumezanu, Qianying Ren, Yuncong Chen, Takehiko Mizoguchi, Dongjin Song, Haifeng Chen

In this paper, we propose an ordered time series classification framework that is robust against missing classes in the training data, i. e., during testing we can prescribe classes that are missing during training.

Missing Labels Retrieval +3