Search Results for author: Jiawei Zhu

Found 20 papers, 8 papers with code

Causal invariant geographic network representations with feature and structural distribution shifts

no code implementations25 Mar 2025 YuHan Wang, Silu He, Qinyao Luo, Hongyuan Yuan, Ling Zhao, Jiawei Zhu, Haifeng Li

We propose a feature-structure mixed invariant representation learning (FSM-IRL) model that accounts for both feature distribution shifts and structural distribution shifts.

Easing Seasickness through Attention Redirection with a Mindfulness-Based Brain--Computer Interface

no code implementations15 Jan 2025 Xiaoyu Bao, Kailin Xu, Jiawei Zhu, Haiyun Huang, Kangning Li, Qiyun Huang, Yuanqing Li

In this study, we propose a mindfulness brain-computer interface (BCI), specifically designed to redirect attention with the aim of mitigating seasickness symptoms in real-world settings.

Brain Computer Interface EEG

GeoAI-Enhanced Community Detection on Spatial Networks with Graph Deep Learning

1 code implementation23 Nov 2024 Yunlei Liang, Jiawei Zhu, Wen Ye, Song Gao

The region2vec methods generate node neural embeddings based on attribute similarity, geographic adjacency and spatial interactions, and then extract network communities based on node embeddings using agglomerative clustering.

Attribute Community Detection +2

An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Large-Scale Recommender Systems

no code implementations18 Sep 2024 Peng Liu, Jiawei Zhu, Cong Xu, Ming Zhao, Bin Wang

However, limited by their modeling pattern, all the current RL-MTF methods can only utilize user features as the state to generate actions for each user, but unable to make use of item features and other valuable features, which leads to suboptimal results.

Multi-Task Learning Recommendation Systems +1

P/D-Serve: Serving Disaggregated Large Language Model at Scale

no code implementations15 Aug 2024 Yibo Jin, Tao Wang, Huimin Lin, Mingyang Song, Peiyang Li, Yipeng Ma, Yicheng Shan, Zhengfan Yuan, Cailong Li, Yajing Sun, Tiandeng Wu, Xing Chu, Ruizhi Huan, Li Ma, Xiao You, Wenting Zhou, Yunpeng Ye, Wen Liu, Xiangkun Xu, Yongsheng Zhang, Tiantian Dong, Jiawei Zhu, Zhe Wang, Xijian Ju, Jianxun Song, Haoliang Cheng, Xiaojing Li, Jiandong Ding, Hefei Guo, Zhengyong Zhang

To overcome previous problems, this paper proposes an end-to-end system P/D-Serve, complying with the paradigm of MLOps (machine learning operations), which models end-to-end (E2E) P/D performance and enables: 1) fine-grained P/D organization, mapping the service with RoCE (RDMA over converged ethernet) as needed, to facilitate similar processing and dynamic adjustments on P/D ratios; 2) on-demand forwarding upon rejections for idle prefill, decoupling the scheduler from regular inaccurate reports and local queues, to avoid timeouts in prefill; and 3) efficient KVCache transfer via optimized D2D access.

Language Modeling Language Modelling +1

An Offline Reinforcement Learning Algorithm Customized for Multi-Task Fusion in Large-Scale Recommender Systems

no code implementations19 Apr 2024 Peng Liu, Cong Xu, Ming Zhao, Jiawei Zhu, Bin Wang, Yi Ren

IntegratedRL-MTF integrates offline RL model with our online exploration policy to relax overstrict and complicated constraints, which significantly improves its performance.

Efficient Exploration Multi-Task Learning +3

Deep Learning-Based Frequency Offset Estimation

no code implementations8 Nov 2023 Tao Chen, Shilian Zheng, Jiawei Zhu, Qi Xuan, Xiaoniu Yang

In wireless communication systems, the asynchronization of the oscillators in the transmitter and the receiver along with the Doppler shift due to relative movement may lead to the presence of carrier frequency offset (CFO) in the received signals.

Deep Learning

Region2Vec: Community Detection on Spatial Networks Using Graph Embedding with Node Attributes and Spatial Interactions

2 code implementations10 Oct 2022 Yunlei Liang, Jiawei Zhu, Wen Ye, Song Gao

Community Detection algorithms are used to detect densely connected components in complex networks and reveal underlying relationships among components.

Attribute Community Detection +2

Curvature Graph Neural Network

no code implementations30 Jun 2021 Haifeng Li, Jun Cao, Jiawei Zhu, Yu Liu, Qing Zhu, Guohua Wu

And we propose Curvature Graph Neural Network (CGNN), which effectively improves the adaptive locality ability of GNNs by leveraging the structural property of graph curvature.

Graph Neural Network Node Classification

Graph Information Vanishing Phenomenon inImplicit Graph Neural Networks

no code implementations2 Mar 2021 Haifeng Li, Jun Cao, Jiawei Zhu, Qing Zhu, Guohua Wu

A class of GNNs solves this problem by learning implicit weights to represent the importance of neighbor nodes, which we call implicit GNNs such as Graph Attention Network.

Graph Attention

KST-GCN: A Knowledge-Driven Spatial-Temporal Graph Convolutional Network for Traffic Forecasting

1 code implementation26 Nov 2020 Jiawei Zhu, Xin Han, Hanhan Deng, Chao Tao, Ling Zhao, Pu Wang, Lin Tao, Haifeng Li

On this background, this study presents a knowledge representation-driven traffic forecasting method based on spatial-temporal graph convolutional networks.

Knowledge Graphs Representation Learning

RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification

no code implementations28 Sep 2020 Haifeng Li, Zhenqi Cui, Zhiqing Zhu, Li Chen, Jiawei Zhu, Haozhe Huang, Chao Tao

On the one hand, RS-MetaNet raises the level of learning from the sample to the task by organizing training in a meta way, and it learns to learn a metric space that can well classify remote sensing scenes from a series of tasks.

General Classification Metric Learning +1

A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting

2 code implementations20 Jun 2020 Jiawei Zhu, Yujiao Song, Ling Zhao, Haifeng Li

In this study, an attention temporal graph convolutional network (A3T-GCN) traffic forecasting method was proposed to simultaneously capture global temporal dynamics and spatial correlations.

Time Series Time Series Analysis

Learning to Measure Change: Fully Convolutional Siamese Metric Networks for Scene Change Detection

2 code implementations22 Oct 2018 Enqiang Guo, Xinsha Fu, Jiawei Zhu, Min Deng, Yu Liu, Qing Zhu, Haifeng Li

A critical challenge problem of scene change detection is that noisy changes generated by varying illumination, shadows and camera viewpoint make variances of a scene difficult to define and measure since the noisy changes and semantic ones are entangled.

Change Detection Scene Change Detection

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