48 citations · 57 across the 7 of their papers we have counts for
7 papers
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…
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…
Model Embedding Model-Based Reinforcement Learning
Xiaoyu Tan, Chao Qu, Junwu Xiong +1
Model-based reinforcement learning (MBRL) has shown its advantages in sample-efficiency over model-free reinforcement learning (MFRL). Despite the impressive results it achieves, i…
Neural Physicist: Learning Physical Dynamics from Image Sequences
Baocheng Zhu, Shijun Wang, James Zhang
We present a novel architecture named Neural Physicist (NeurPhy) to learn physical dynamics directly from image sequences using deep neural networks. For any physical system, given…