Search Results for author: Shuai Xiao

Found 11 papers, 5 papers with code

Model-based Constrained MDP for Budget Allocation in Sequential Incentive Marketing

no code implementations2 Mar 2023 Shuai Xiao, Le Guo, Zaifan Jiang, Lei Lv, Yuanbo Chen, Jun Zhu, Shuang Yang

Furthermore, we show that the dual problem can be solved by policy learning, with the optimal dual variable being found efficiently via bisection search (i. e., by taking advantage of the monotonicity).


SJ-HD^2R: Selective Joint High Dynamic Range and Denoising Imaging for Dynamic Scenes

no code implementations20 Jun 2022 Wei Li, Shuai Xiao, Tianhong Dai, Shanxin Yuan, Tao Wang, Cheng Li, Fenglong Song

To further leverage these two paradigms, we propose a selective and joint HDR and denoising (SJ-HD$^2$R) imaging framework, utilizing scenario-specific priors to conduct the path selection with an accuracy of more than 93. 3$\%$.


Learning Temporal Point Processes via Reinforcement Learning

no code implementations NeurIPS 2018 Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song

Social goods, such as healthcare, smart city, and information networks, often produce ordered event data in continuous time.

Point Processes reinforcement-learning +1

Modeling The Intensity Function Of Point Process Via Recurrent Neural Networks

2 code implementations24 May 2017 Shuai Xiao, Junchi Yan, Stephen M. Chu, Xiaokang Yang, Hongyuan Zha

In this paper, we model the background by a Recurrent Neural Network (RNN) with its units aligned with time series indexes while the history effect is modeled by another RNN whose units are aligned with asynchronous events to capture the long-range dynamics.

Point Processes Time Series Analysis

Wasserstein Learning of Deep Generative Point Process Models

1 code implementation NeurIPS 2017 Shuai Xiao, Mehrdad Farajtabar, Xiaojing Ye, Junchi Yan, Le Song, Hongyuan Zha

Point processes are becoming very popular in modeling asynchronous sequential data due to their sound mathematical foundation and strength in modeling a variety of real-world phenomena.

Point Processes

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