Published in IPCCC 2025, 2025
This paper proposes a DRL based TCP congestion control framework, which caters to handle various objectives (maximize throughput, minimize latency, …) set by various applications.
Published in AAAI 2026, Under Review, 2025
The paper introduces NetSight, a model that captures global-local spatial-temporal dependencies through a data-driven fusion graph, node normalization, and multi-head attention, significantly improving network traffic forecasting accuracy.
Published in Applied Soft Computing, 2022
In this paper, for semi-supervised learning, we propose a new framework WFRSTT, which incorporates the merits of Fuzzy Rough Sets, Tri-training, a novel noise-filtering technique bad-points, and the multi-view information. Experiment results demonstrate its effectiveness in Medical Diagnosis.