Search Results for author: Jing Zhu

Found 28 papers, 8 papers with code

Hybrid Beamforming for RIS-Assisted Multiuser Fluid Antenna Systems

no code implementations12 Apr 2025 Jiangong Chen, Yue Xiao, Zhendong Peng, Jing Zhu, Xia Lei, Christos Masouros, Kai-Kit Wong

Recent advances in reconfigurable antennas have led to the new concept of the fluid antenna system (FAS) for shape and position flexibility, as another degree of freedom for wireless communication enhancement.

Position

Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics

no code implementations30 Mar 2025 Jing Zhu, Mingxuan Ju, Yozen Liu, Danai Koutra, Neil Shah, Tong Zhao

Generative recommendation (GR) has become a powerful paradigm in recommendation systems that implicitly links modality and semantics to item representation, in contrast to previous methods that relied on non-semantic item identifiers in autoregressive models.

Recommendation Systems

Amplitude-Domain Reflection Modulation for Active RIS-Assisted Wireless Communications

no code implementations27 Mar 2025 Jing Zhu, Qu, Luo, Zheng Chu, Gaojie Chen, Pei Xiao, Lixia Xiao, Chaoyun Song

In this paper, we propose a novel active reconfigurable intelligent surface (RIS)-assisted amplitude-domain reflection modulation (ADRM) transmission scheme, termed as ARIS-ADRM.

Joint Sparse Graph for Enhanced MIMO-AFDM Receiver Design

no code implementations24 Mar 2025 Qu Luo, Jing Zhu, Zilong Liu, Yanqun Tang, Pei Xiao, Gaojie Chen, Jia Shi

This paper is devoted to enhanced receiver design for multiple input and multiple output AFDM (MIMO-AFDM) systems.

Variational Inference

Single Sparse Graph Enhanced Expectation Propagation Algorithm Design for Uplink MIMO-SCMA

no code implementations17 Mar 2025 Qu Luo, Jing Zhu, Gaojie Chen, Pei Xiao, Rahim Tafazolli

Sparse code multiple access (SCMA) and multiple input multiple output (MIMO) are considered as two efficient techniques to provide both massive connectivity and high spectrum efficiency for future machine-type wireless networks.

Advanced Nonlinear SCMA Codebook Design Based on Lattice Constellations

no code implementations13 Nov 2024 Qu Luo, Jing Zhu, Gaojie Chen, Pei Xiao, Rahim Tafazolli

This mapping is referred to as nonlinear mapping (codebook) in this paper.

NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation

1 code implementation30 Oct 2024 Momin Haider, Ming Yin, Menglei Zhang, Arpit Gupta, Jing Zhu, Yu-Xiang Wang

Mobile devices such as smartphones, laptops, and tablets can often connect to multiple access networks (e. g., Wi-Fi, LTE, and 5G) simultaneously.

D4RL Management +1

On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks

no code implementations26 Sep 2024 Jiong Zhu, Gaotang Li, Yao-An Yang, Jing Zhu, Xuehao Cui, Danai Koutra

Heterophily, or the tendency of connected nodes in networks to have different class labels or dissimilar features, has been identified as challenging for many Graph Neural Network (GNN) models.

Graph Learning Graph Neural Network +3

Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning

no code implementations24 Jun 2024 Jing Zhu, YuHang Zhou, Shengyi Qian, Zhongmou He, Tong Zhao, Neil Shah, Danai Koutra

Graph machine learning has made significant strides in recent years, yet the integration of visual information with graph structure and its potential for improving performance in downstream tasks remains an underexplored area.

Graph Learning

Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation

1 code implementation19 Jun 2024 YuHang Zhou, Jing Zhu, Paiheng Xu, Xiaoyu Liu, Xiyao Wang, Danai Koutra, Wei Ai, Furong Huang

Large language models (LLMs) have significantly advanced various natural language processing tasks, but deploying them remains computationally expensive.

Knowledge Distillation

BClean: A Bayesian Data Cleaning System

1 code implementation11 Nov 2023 Jianbin Qin, Sifan Huang, Yaoshu Wang, Jing Zhu, Yifan Zhang, Yukai Miao, Rui Mao, Makoto Onizuka, Chuan Xiao

By evaluating on both real-world and synthetic datasets, we demonstrate that BClean is capable of achieving an F-measure of up to 0. 9 in data cleaning, outperforming existing Bayesian methods by 2% and other data cleaning methods by 15%.

Bayesian Inference graph partitioning

Spatial Attention-based Distribution Integration Network for Human Pose Estimation

no code implementations9 Nov 2023 Sihan Gao, Jing Zhu, Xiaoxuan Zhuang, Zhaoyue Wang, Qijin Li

The RFM incorporates a dilated residual block and attention mechanism to expand receptive fields while enhancing sensitivity to spatial information.

Pose Estimation

TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning

1 code implementation25 Sep 2023 Jing Zhu, Xiang Song, Vassilis N. Ioannidis, Danai Koutra, Christos Faloutsos

How can we enhance the node features acquired from Pretrained Models (PMs) to better suit downstream graph learning tasks?

Domain Adaptation Graph Learning +2

Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices

no code implementations1 Jun 2023 Jing Zhu, YuHang Zhou, Vassilis N. Ioannidis, Shengyi Qian, Wei Ai, Xiang Song, Danai Koutra

While Graph Neural Networks (GNNs) are remarkably successful in a variety of high-impact applications, we demonstrate that, in link prediction, the common practices of including the edges being predicted in the graph at training and/or test have outsized impact on the performance of low-degree nodes.

Link Prediction Node Classification

Touch and Go: Learning from Human-Collected Vision and Touch

no code implementations22 Nov 2022 Fengyu Yang, Chenyang Ma, Jiacheng Zhang, Jing Zhu, Wenzhen Yuan, Andrew Owens

The ability to associate touch with sight is essential for tasks that require physically interacting with objects in the world.

Image Stylization

Weight-based Channel-model Matrix Framework provides a reasonable solution for EEG-based cross-dataset emotion recognition

no code implementations13 Sep 2022 Huayu Chen, Huanhuan He, Jing Zhu, Shuting Sun, Jianxiu Li, Xuexiao Shao, Junxiang Li, Xiaowei Li, Bin Hu

Cross-dataset emotion recognition as an extremely challenging task in the field of EEG-based affective computing is influenced by many factors, which makes the universal models yield unsatisfactory results.

EEG Emotion Recognition

CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment

1 code implementation23 Aug 2022 Jing Zhu, Danai Koutra, Mark Heimann

Network alignment, or the task of finding corresponding nodes in different networks, is an important problem formulation in many application domains.

Debiasing pipeline improves deep learning model generalization for X-ray based lung nodule detection

no code implementations24 Jan 2022 Michael Horry, Subrata Chakraborty, Biswajeet Pradhan, Manoranjan Paul, Jing Zhu, Hui Wen Loh, Prabal Datta Barua, U. Rajendra Arharya

In stripping chest X-ray images of known confounding variables by lung field segmentation, along with suppression of signal noise from the bone structure we can train a highly accurate deep learning lung nodule detection algorithm with outstanding generalization accuracy of 89% to nodule samples in unseen data.

Deep Learning Lung Nodule Detection +1

ContinuityLearner: Geometric Continuity Feature Learning for Lane Segmentation

no code implementations7 Aug 2021 HaoYu Fang, Jing Zhu, Yi Fang

Lane segmentation is a challenging issue in autonomous driving system designing because lane marks show weak textural consistency due to occlusion or extreme illumination but strong geometric continuity in traffic images, from which general convolution neural networks (CNNs) are not capable of learning semantic objects.

Autonomous Driving Segmentation

Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding

1 code implementation26 Feb 2021 Jing Zhu, Xingyu Lu, Mark Heimann, Danai Koutra

While most network embedding techniques model the relative positions of nodes in a network, recently there has been significant interest in structural embeddings that model node role equivalences, irrespective of their distances to any specific nodes.

All Graph Embedding +1

Modeling Long-Term and Short-Term Interests with Parallel Attentions for Session-based Recommendation

no code implementations27 Jun 2020 Jing Zhu, Yanan Xu, Yanmin Zhu

First, most of the attention-based methods only simply utilize the last clicked item to represent the user's short-term interest ignoring the temporal information and behavior context, which may fail to capture the recent preference of users comprehensively.

Session-Based Recommendations

MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

no code implementations20 Feb 2020 Hanshu Cai, Yiwen Gao, Shuting Sun, Na Li, Fuze Tian, Han Xiao, Jianxiu Li, Zhengwu Yang, Xiaowei Li, Qinglin Zhao, Zhenyu Liu, Zhijun Yao, Minqiang Yang, Hong Peng, Jing Zhu, Xiaowei Zhang, Guoping Gao, Fang Zheng, Rui Li, Zhihua Guo, Rong Ma, Jing Yang, Lan Zhang, Xiping Hu, Yumin Li, Bin Hu

The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications.

EEG

Structure-Attentioned Memory Network for Monocular Depth Estimation

no code implementations10 Sep 2019 Jing Zhu, Yunxiao Shi, Mengwei Ren, Yi Fang, Kuo-Chin Lien, Junli Gu

To this end, we introduce a new Structure-Oriented Memory (SOM) module to learn and memorize the structure-specific information between RGB image domain and the depth domain.

Domain Adaptation Monocular Depth Estimation

Learning Object-specific Distance from a Monocular Image

no code implementations ICCV 2019 Jing Zhu, Yi Fang, Husam Abu-Haimed, Kuo-Chin Lien, Dongdong Fu, Junli Gu

Environment perception, including object detection and distance estimation, is one of the most crucial tasks for autonomous driving.

Autonomous Driving Object +2

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