activity
20202023
most citedA Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud

48 citations · 69 across the 6 of their papers we have counts for

collaborators

6 papers

cs.DC2023★ 6 cited

Full Scaling Automation for Sustainable Development of Green Data Centers

Shiyu Wang, Yinbo Sun, Xiaoming Shi +5

The rapid rise in cloud computing has resulted in an alarming increase in data centers' carbon emissions, which now accounts for >3% of global greenhouse gas emissions, necessitati…

cs.LG2023★ 1 cited

SLOTH: Structured Learning and Task-based Optimization for Time Series Forecasting on Hierarchies

Fan Zhou, Chen Pan, Lintao Ma +9

Multivariate time series forecasting with hierarchical structure is widely used in real-world applications, e.g., sales predictions for the geographical hierarchy formed by cities,…

cs.LG2022★ 10 cited

End-to-End Modeling Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow based Reconciliation

Shiyu Wang, Fan Zhou, Yinbo Sun +3

Multivariate time series forecasting with hierarchical structure is pervasive in real-world applications, demanding not only predicting each level of the hierarchy, but also reconc…

cs.LG2022★ 4 cited

A Graph Regularized Point Process Model For Event Propagation Sequence

Siqiao Xue, Xiaoming Shi, Hongyan Hao +4

Point process is the dominant paradigm for modeling event sequences occurring at irregular intervals. In this paper we aim at modeling latent dynamics of event propagation in graph…

cs.LG2022★ 48 cited

A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud

Siqiao Xue, Chao Qu, Xiaoming Shi +11

Predictive autoscaling (autoscaling with workload forecasting) is an important mechanism that supports autonomous adjustment of computing resources in accordance with fluctuating w…

cs.LG2020

FADACS: A Few-shot Adversarial Domain Adaptation Architecture for Context-Aware Parking Availability Sensing

Wei Shao, Sichen Zhao, Zhen Zhang +4

Existing research on parking availability sensing mainly relies on extensive contextual and historical information. In practice, the availability of such information is a challenge…