M
Mingxi Cheng
Researcher at University of Southern California
Publications - 14
Citations - 274
Mingxi Cheng is an academic researcher from University of Southern California. The author has contributed to research in topics: Rumor & Cloud computing. The author has an hindex of 6, co-authored 14 publications receiving 143 citations. Previous affiliations of Mingxi Cheng include Duke University.
Papers
More filters
Proceedings ArticleDOI
DRL-cloud: deep reinforcement learning-based resource provisioning and task scheduling for cloud service providers
TL;DR: DRL-Cloud is presented, a novel Deep Reinforcement Learning (DRL)-based RP and TS system, to minimize energy cost for large-scale CSPs with very large number of servers that receive enormous numbers of user requests per day.
Proceedings ArticleDOI
VRoC: Variational Autoencoder-aided Multi-task Rumor Classifier Based on Text
TL;DR: The proposed VRoC, a tweet-level variational autoencoder-based rumor classification system, consistently outperforms several state-of-the-art techniques, on both observed and unobserved rumors, by up to 26.9%, in terms of macro-F1 scores.
Journal ArticleDOI
A COVID-19 Rumor Dataset
Journal ArticleDOI
There Is Hope After All: Quantifying Opinion and Trustworthiness in Neural Networks.
TL;DR: DeepTrust identifies proper multi-layered neural network (NN) topologies that have high projected trust probabilities, even when trained with untrusted data, and shows that uncertain opinion of data is not always malicious while evaluating NN's opinion and trustworthiness, whereas the disbelief opinion hurts trust the most.
Journal ArticleDOI
H₂O-Cloud: A Resource and Quality of Service-Aware Task Scheduling Framework for Warehouse-Scale Data Centers
TL;DR: The proposed H2O-Cloud is highly scalable and considers comprehensive information, such as various workload scenarios, cloud platform configurations, user request information, and dynamic pricing model, to improve resource usage effectiveness while maintaining quality of service (QoS).