142 citations · 217 across the 12 of their papers we have counts for
12 papers
Temporal aware Multi-Interest Graph Neural Network For Session-based Recommendation
Qi Shen, Shixuan Zhu, Yitong Pang +2
Session-based recommendation (SBR) is a challenging task, which aims at recommending next items based on anonymous interaction sequences. Despite the superior performance of existi…
Automatic Configuration for Optimal Communication Scheduling in DNN Training
Yiqing Ma, Hao Wang, Yiming Zhang +1
ByteScheduler partitions and rearranges tensor transmissions to improve the communication efficiency of distributed Deep Neural Network (DNN) training. The configuration of hyper-p…
Intention Adaptive Graph Neural Network for Category-aware Session-based Recommendation
Chuan Cui, Qi Shen, Shixuan Zhu +4
Session-based recommendation (SBR) is proposed to recommend items within short sessions given that user profiles are invisible in various scenarios nowadays, such as e-commerce and…
Aggressive Q-Learning with Ensembles: Achieving Both High Sample Efficiency and High Asymptotic Performance
Yanqiu Wu, Xinyue Chen, Che Wang +2
Recent advances in model-free deep reinforcement learning (DRL) show that simple model-free methods can be highly effective in challenging high-dimensional continuous control tasks…
Multi-behavior Graph Contextual Aware Network for Session-based Recommendation
Qi Shen, Lingfei Wu, Yitong Pang +4
Predicting the next interaction of a short-term sequence is a challenging task in session-based recommendation (SBR).Multi-behavior session recommendation considers session sequenc…
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation
Yitong Pang, Lingfei Wu, Qi Shen +6
Predicting the next interaction of a short-term interaction session is a challenging task in session-based recommendation. Almost all existing works rely on item transition pattern…
On-Policy Deep Reinforcement Learning for the Average-Reward Criterion
Yiming Zhang, Keith W. Ross
We develop theory and algorithms for average-reward on-policy Reinforcement Learning (RL). We first consider bounding the difference of the long-term average reward for two policie…
AinnoSeg: Panoramic Segmentation with High Perfomance
Jiahong Wu, Jianfei Lu, Xinxin Kang +7
Panoramic segmentation is a scene where image segmentation tasks is more difficult. With the development of CNN networks, panoramic segmentation tasks have been sufficiently develo…
MLCVNet: Multi-Level Context VoteNet for 3D Object Detection
Qian Xie, Yu-Kun Lai, Jing Wu +4
In this paper, we address the 3D object detection task by capturing multi-level contextual information with the self-attention mechanism and multi-scale feature fusion. Most existi…
Locality-Sensitive Sketching for Resilient Network Flow Monitoring
Yongquan Fu, Dongsheng Li, Siqi Shen +2
Network monitoring is vital in modern clouds and data center networks for traffic engineering, network diagnosis, network intrusion detection, which need diverse traffic statistics…
Efficient Entropy for Policy Gradient with Multidimensional Action Space
Yiming Zhang, Quan Ho Vuong, Kenny Song +2
In recent years, deep reinforcement learning has been shown to be adept at solving sequential decision processes with high-dimensional state spaces such as in the Atari games. Many…
Multi-Fidelity Surrogate Based on Single Linear Regression
Yiming Zhang, Nam-Ho Kim, Chanyoung Park +1
Various frameworks have been proposed to predict mechanical system responses by combining data from different fidelities for design optimization and uncertainty quantification as r…