activity
20182023
most citedA Robust and Efficient Multi-Scale Seasonal-Trend Decomposition

19 citations · 27 across the 8 of their papers we have counts for

collaborators

12 papers

cs.LG2024

Evolving Multi-Scale Normalization for Time Series Forecasting under Distribution Shifts

Dalin Qin, Yehui Li, Weiqi Chen +5

Complex distribution shifts are the main obstacle to achieving accurate long-term time series forecasting. Several efforts have been conducted to capture the distribution character…

cs.LG2023

SaDI: A Self-adaptive Decomposed Interpretable Framework for Electric Load Forecasting under Extreme Events

Hengbo Liu, Ziqing Ma, Linxiao Yang +5

Accurate prediction of electric load is crucial in power grid planning and management. In this paper, we solve the electric load forecasting problem under extreme events such as sc…

cs.DC2022

RobustScaler: QoS-Aware Autoscaling for Complex Workloads

Huajie Qian, Qingsong Wen, Liang Sun +3

Autoscaling is a critical component for efficient resource utilization with satisfactory quality of service (QoS) in cloud computing. This paper investigates proactive autoscaling…

cs.LG2022

NetRCA: An Effective Network Fault Cause Localization Algorithm

Chaoli Zhang, Zhiqiang Zhou, Yingying Zhang +4

Localizing the root cause of network faults is crucial to network operation and maintenance. However, due to the complicated network architectures and wireless environments, as wel…

cs.DC20211 cited

CloudRCA: A Root Cause Analysis Framework for Cloud Computing Platforms

Yingying Zhang, Zhengxiong Guan, Huajie Qian +7

As business of Alibaba expands across the world among various industries, higher standards are imposed on the service quality and reliability of big data cloud computing platforms…

stat.AP202119 cited

A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition

Linxiao Yang, Qingsong Wen, Bo Yang +1

Many real-world time series exhibit multiple seasonality with different lengths. The removal of seasonal components is crucial in numerous applications of time series, including fo…