Jun Guo

U-TRI

2017

Traffic analysis within switches is threatening the security of large enterprise networks built with SDN. Adversaries are able to monitor all traffic traversing a switch by exploiting just one vulnerability in it and obtain linkage …

Study on Dispatching Decision Information of Power Flow Distribution Under Wildfire Disasters

2019

The dispatching decision information of power flow distribution under the wildfire disaster needs to consider the disturbance of the internal fault of the power grid and the influence of external factors. Aiming at the current …

PMD: An Optimal Transportation-based User Distance for Recommender Systems

2019 · arXiv (Cornell University)

Collaborative filtering, a widely-used recommendation technique, predicts a user's preference by aggregating the ratings from similar users. As a result, these measures cannot fully utilize the rating information and are not suitable for real world …

A Joint Model for Dropped Pronoun Recovery and Conversational Discourse Parsing in Chinese Conversational Speech

2021 · arXiv (Cornell University)

In this paper, we present a neural model for joint dropped pronoun recovery (DPR) and conversational discourse parsing (CDP) in Chinese conversational speech. We show that DPR and CDP are closely related, and a joint …

Research on a Virtual Machine Mode Transfer Method Supporting Energy Consumption Optimization

2022 · 2022 24th International Conference on Advanced Communication Technology (ICACT)

In traditional cloud resource optimization scheduling, excessive pursuit of service performance and system reliability has resulted in low utilization of system resources and severe energy dissipation. In this paper, transfer target of virtual machines was …

Towards Comprehensive Testing on the Robustness of Cooperative Multi-agent Reinforcement Learning

2022 · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

While deep neural networks (DNNs) have strengthened the performance of cooperative multi-agent reinforcement learning (c-MARL), the agent policy can be easily perturbed by adversarial examples. Considering the safety critical applications of c-MARL, such as traffic …