3 papers
cs.LG2025
Shared Representation Learning for High-Dimensional Multi-Task Forecasting under Resource Contention in Cloud-Native Backends
Zixiao Huang, Jixiao Yang, Sijia Li +3
This study proposes a unified forecasting framework for high-dimensional multi-task time series to meet the prediction demands of cloud native backend systems operating under highl…
cs.LG2025
Cost-TrustFL: Cost-Aware Hierarchical Federated Learning with Lightweight Reputation Evaluation across Multi-Cloud
Jixiao Yang, Jinyu Chen, Zixiao Huang +3
Federated learning across multi-cloud environments faces critical challenges, including non-IID data distributions, malicious participant detection, and substantial cross-cloud com…
stat.ML2025
Label-shift robust federated feature screening for high-dimensional classification
Qi Qin, Erbo Li, Xingxiang Li +3
Distributed and federated learning are important tools for high-dimensional classification of large datasets. To reduce computational costs and overcome the curse of dimensionality…