48 citations · 99 across the 17 of their papers we have counts for
7 papers · 1 filter
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 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…
Digital Human Interactive Recommendation Decision-Making Based on Reinforcement Learning
Xiong Junwu, Xiaoyun Feng, YunZhou Shi +3
Digital human recommendation system has been developed to help customers find their favorite products and is playing an active role in various recommendation contexts. How to timel…
HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event Sequences
Siqiao Xue, Xiaoming Shi, James Y Zhang +1
In this paper, we tackle the important yet under-investigated problem of making long-horizon prediction of event sequences. Existing state-of-the-art models do not perform well at…
Learning Large-scale Universal User Representation with Sparse Mixture of Experts
Caigao Jiang, Siqiao Xue, James Zhang +3
Learning user sequence behaviour embedding is very sophisticated and challenging due to the complicated feature interactions over time and high dimensions of user features. Recent…
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…
Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processes
Chao Qu, Xiaoyu Tan, Siqiao Xue +3
We consider a sequential decision making problem where the agent faces the environment characterized by the stochastic discrete events and seeks an optimal intervention policy such…