48 citations · 63 across the 7 of their papers we have counts for
6 papers
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting
Fan Zhou, Chen Pan, Lintao Ma +9
Time series forecasts of different temporal granularity are widely used in real-world applications, e.g., sales prediction in days and weeks for making different inventory plans. H…
Deep Optimal Timing Strategies for Time Series
Chen Pan, Fan Zhou, Xuanwei Hu +6
Deciding the best future execution time is a critical task in many business activities while evolving time series forecasting, and optimal timing strategy provides such a solution,…
Automatic Deduction Path Learning via Reinforcement Learning with Environmental Correction
Shuai Xiao, Chen Pan, Min Wang +6
Automatic bill payment is an important part of business operations in fintech companies. The practice of deduction was mainly based on the total amount or heuristic search by divid…
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,…
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…
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…