213 citations · 427 across the 24 of their papers we have counts for
16 papers · 1 filter
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations
Tianxiang Zhao, Wenchao Yu, Suhang Wang +6
Imitation learning has achieved great success in many sequential decision-making tasks, in which a neural agent is learned by imitating collected human demonstrations. However, exi…
Personalized Federated Learning via Heterogeneous Modular Networks
Tianchun Wang, Wei Cheng, Dongsheng Luo +5
Personalized Federated Learning (PFL) which collaboratively trains a federated model while considering local clients under privacy constraints has attracted much attention. Despite…
Deep Federated Anomaly Detection for Multivariate Time Series Data
Wei Zhu, Dongjin Song, Yuncong Chen +6
Despite the fact that many anomaly detection approaches have been developed for multivariate time series data, limited effort has been made on federated settings in which multivari…
Ordinal-Quadruplet: Retrieval of Missing Classes in Ordinal Time Series
Jurijs Nazarovs, Cristian Lumezanu, Qianying Ren +4
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…
InfoGCL: Information-Aware Graph Contrastive Learning
Dongkuan Xu, Wei Cheng, Dongsheng Luo +2
Various graph contrastive learning models have been proposed to improve the performance of learning tasks on graph datasets in recent years. While effective and prevalent, these mo…
Learning Disentangled Representations for Time Series
Yuening Li, Zhengzhang Chen, Daochen Zha +4
Time-series representation learning is a fundamental task for time-series analysis. While significant progress has been made to achieve accurate representations for downstream appl…