Search Results for author: Qian Ma

Found 11 papers, 1 papers with code

Holography inspired self-controlled reconfigurable intelligent surface

no code implementations24 Mar 2024 Jieao Zhu, Ze Gu, Qian Ma, Linglong Dai, Tie Jun Cui

Among various promising candidate technologies for the sixth-generation (6G) wireless communications, recent advances in microwave metasurfaces have sparked a new research area of reconfigurable intelligent surfaces (RISs).

Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks

no code implementations24 Feb 2024 Qian Ma, Hongliang Chi, Hengrui Zhang, Kay Liu, Zhiwei Zhang, Lu Cheng, Suhang Wang, Philip S. Yu, Yao Ma

The rise of self-supervised learning, which operates without the need for labeled data, has garnered significant interest within the graph learning community.

Contrastive Learning Graph Learning +1

Multiperson Detection and Vital-Sign Sensing Empowered by Space-Time-Coding RISs

no code implementations15 Jan 2024 Xinyu Li, Jian Wei You, Ze Gu, Qian Ma, Jingyuan Zhang, Long Chen, Tie Jun Cui

Passive human sensing using wireless signals has attracted increasing attention due to its superiorities of non-contact and robustness in various lighting conditions.

Human Detection

Passive Human Sensing Enhanced by Reconfigurable Intelligent Surface: Opportunities and Challenges

no code implementations14 Nov 2023 Xinyu Li, Jian Wei You, Ze Gu, Qian Ma, Long Chen, Jingyuan Zhang, Shi Jin, Tie Jun Cui

Reconfigurable intelligent surfaces (RISs) have flexible and exceptional performance in manipulating electromagnetic waves and customizing wireless channels.

Activity Recognition

Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting

1 code implementation20 Sep 2023 Qian Ma, Zijian Zhang, Xiangyu Zhao, Haoliang Li, Hongwei Zhao, Yiqi Wang, Zitao Liu, Wanyu Wang

Then, we generate representative and common spatio-temporal patterns as global nodes to reflect a global dependency between sensors and provide auxiliary information for spatio-temporal dependency learning.

PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction

no code implementations18 Sep 2023 Zijian Zhang, Xiangyu Zhao, Qidong Liu, Chunxu Zhang, Qian Ma, Wanyu Wang, Hongwei Zhao, Yiqi Wang, Zitao Liu

We devise a spatio-temporal transformer and a parameter-sharing training scheme to address the common knowledge among different spatio-temporal attributes.

Attribute

Dimensionality Reduced Antenna Array for Beamforming/steering

no code implementations28 Oct 2022 Shiyi Xia, Mingyang Zhao, Qian Ma, Xunnan Zhang, Ling Yang, Yazhi Pi, Hyunchul Chung, Ad Reniers, A. M. J. Koonen, Zizheng Cao

Finally, the 16/8/4 -array beam steering was demonstrated by using 4/3/2 active controllers, respectively.

Collaboration in Participant-Centric Federated Learning: A Game-Theoretical Perspective

no code implementations25 Jul 2022 Guangjing Huang, Xu Chen, Tao Ouyang, Qian Ma, Lin Chen, Junshan Zhang

To coordinate the selfish and heterogeneous participants, we propose a novel analytic framework for incentivizing effective and efficient collaborations for participant-centric FL.

Federated Learning

Enabling Long-Term Cooperation in Cross-Silo Federated Learning: A Repeated Game Perspective

no code implementations22 Jun 2021 Ning Zhang, Qian Ma, Xu Chen

We show that enforced by a punishment strategy, such a cooperative strategy is a subgame perfect Nash equilibrium (SPNE) of the infinitely repeated game, under which some clients who are free riders at the NE of the stage game choose to be (partial) contributors.

Federated Learning

Multiple Dynamic Pricing for Demand Response with Adaptive Clustering-based Customer Segmentation in Smart Grids

no code implementations10 Jun 2021 Fanlin Meng, Qian Ma, Zixu Liu, Xiao-jun Zeng

In this paper, we propose a realistic multiple dynamic pricing approach to demand response in the retail market.

Clustering

MulDE: Multi-teacher Knowledge Distillation for Low-dimensional Knowledge Graph Embeddings

no code implementations14 Oct 2020 Kai Wang, Yu Liu, Qian Ma, Quan Z. Sheng

Link prediction based on knowledge graph embeddings (KGE) aims to predict new triples to automatically construct knowledge graphs (KGs).

Knowledge Distillation Knowledge Graph Embedding +2

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