Search Results for author: Jun Wu

Found 46 papers, 12 papers with code

Exploiting Point-Wise Attention in 6D Object Pose Estimation Based on Bidirectional Prediction

no code implementations16 Aug 2023 Yuhao Yang, Jun Wu, Yue Wang, Guangjian Zhang, Rong Xiong

Traditional geometric registration based estimation methods only exploit the CAD model implicitly, which leads to their dependence on observation quality and deficiency to occlusion.

6D Pose Estimation using RGB

Differentially Private Graph Neural Network with Importance-Grained Noise Adaption

no code implementations9 Aug 2023 Yuxin Qi, Xi Lin, Jun Wu

We propose NAP-GNN, a node-importance-grained privacy-preserving GNN algorithm with privacy guarantees based on adaptive differential privacy to safeguard node information.

Graph Learning Privacy Preserving

When UAVs Meet ISAC: Real-Time Trajectory Design for Secure Communications

no code implementations25 Jun 2023 Jun Wu, Weijie Yuan, Lajos Hanzo

The real-time unmanned aerial vehicle (UAV) trajectory design of secure integrated sensing and communication (ISAC) is optimized.

Privacy Inference-Empowered Stealthy Backdoor Attack on Federated Learning under Non-IID Scenarios

no code implementations13 Jun 2023 Haochen Mei, Gaolei Li, Jun Wu, Longfei Zheng

In this paper, we propose a novel privacy inference-empowered stealthy backdoor attack (PI-SBA) scheme for FL under non-IID scenarios.

Backdoor Attack Federated Learning

Optimizing the Collaboration Structure in Cross-Silo Federated Learning

1 code implementation10 Jun 2023 Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He

In federated learning (FL), multiple clients collaborate to train machine learning models together while keeping their data decentralized.

Federated Learning

FakeSwarm: Improving Fake News Detection with Swarming Characteristics

no code implementations30 May 2023 Jun Wu, Xuesong Ye

We evaluate our system on a public dataset and demonstrate the effectiveness of incorporating swarm features in fake news identification, achieving an f1-score and accuracy of over 97% by combining all three types of swarm features.

Fake News Detection

MedLens: Improve Mortality Prediction Via Medical Signs Selecting and Regression

1 code implementation19 May 2023 Xuesong Ye, Jun Wu, Chengjie Mou, Weinan Dai

Monitoring the health status of patients and predicting mortality in advance is vital for providing patients with timely care and treatment.

Mortality Prediction regression +1

FineEHR: Refine Clinical Note Representations to Improve Mortality Prediction

no code implementations24 Apr 2023 Jun Wu, Xuesong Ye, Chengjie Mou, Weinan Dai

To address this issue, we propose FINEEHR, a system that utilizes two representation learning techniques, namely metric learning and fine-tuning, to refine clinical note embeddings, while leveraging the intrinsic correlations among different health statuses and note categories.

Metric Learning Mortality Prediction +1

BotTriNet: A Unified and Efficient Embedding for Social Bots Detection via Metric Learning

no code implementations6 Apr 2023 Jun Wu, Xuesong Ye, Yanyuet Man

Second, we demonstrate that metric learning techniques can be applied in this context to refine raw embeddings and improve classification performance.

Metric Learning

BotShape: A Novel Social Bots Detection Approach via Behavioral Patterns

no code implementations17 Mar 2023 Jun Wu, Xuesong Ye, Chengjie Mou

An essential topic in online social network security is how to accurately detect bot accounts and relieve their harmful impacts (e. g., misinformation, rumor, and spam) on genuine users.

Misinformation Time Series

Non-IID Transfer Learning on Graphs

1 code implementation15 Dec 2022 Jun Wu, Jingrui He, Elizabeth Ainsworth

To bridge the gap, in this paper, we propose rigorous generalization bounds and algorithms for cross-network transfer learning from a source graph to a target graph.

Generalization Bounds Link Prediction +2

Aircraft Ground Taxiing Deduction and Conflict Early Warning Method Based on Control Command Information

no code implementations4 Nov 2022 Jingchang Zhuge, Huiyuan Liang, Yiming Zhang, Shichao Li, Xinyu Yang, Jun Wu

Aircraft taxiing conflict is a threat to the safety of airport operations, mainly due to the human error in control command infor-mation.

RING++: Roto-translation Invariant Gram for Global Localization on a Sparse Scan Map

1 code implementation12 Oct 2022 Xuecheng Xu, Sha Lu, Jun Wu, Haojian Lu, Qiuguo Zhu, Yiyi Liao, Rong Xiong, Yue Wang

In addition, we derive sufficient conditions of feature extractors for the representation preserving the roto-translation invariance, making RING++ a framework applicable to generic multi-channel features.


A Unified Meta-Learning Framework for Dynamic Transfer Learning

1 code implementation5 Jul 2022 Jun Wu, Jingrui He

Transfer learning refers to the transfer of knowledge or information from a relevant source task to a target task.

Meta-Learning Transfer Learning

Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy

no code implementations1 Jul 2022 Jun Wu, Lilu Liu, Yue Wang, Rong Xiong

We ascertain the Mid- Fusion approach is the best approach to restore the most precise 3D keypoints useful for object pose estimation.

6D Pose Estimation using RGB

LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization

no code implementations23 Jun 2022 Honglei Zhang, Fangyuan Luo, Jun Wu, Xiangnan He, Yidong Li

Federated recommender system (FRS), which enables many local devices to train a shared model jointly without transmitting local raw data, has become a prevalent recommendation paradigm with privacy-preserving advantages.

Privacy Preserving Recommendation Systems

Adaptive Transfer Learning for Plant Phenotyping

no code implementations14 Jan 2022 Jun Wu, Elizabeth A. Ainsworth, Sheng Wang, Kaiyu Guan, Jingrui He

Plant phenotyping (Guo et al. 2021; Pieruschka et al. 2019) focuses on studying the diverse traits of plants related to the plants' growth.

BIG-bench Machine Learning GPR +3

Learning Stereopsis from Geometric Synthesis for 6D Object Pose Estimation

no code implementations25 Sep 2021 Jun Wu, Lilu Liu, Yue Wang, Rong Xiong

Current monocular-based 6D object pose estimation methods generally achieve less competitive results than RGBD-based methods, mostly due to the lack of 3D information.

6D Pose Estimation using RGB

RF-LighGBM: A probabilistic ensemble way to predict customer repurchase behaviour in community e-commerce

no code implementations2 Sep 2021 Liping Yang, Xiaxia Niu, Jun Wu

Given the complex problem of feature engineering, the classic model RFM in the field of customer relationship management is improved, and an improved model is proposed to describe the characteristics of customer buying behaviour, which includes five indicators.

Feature Engineering Hyperparameter Optimization +1

Automatically Lock Your Neural Networks When You're Away

no code implementations15 Mar 2021 Ge Ren, Jun Wu, Gaolei Li, Shenghong Li

The smartphone and laptop can be unlocked by face or fingerprint recognition, while neural networks which confront numerous requests every day have little capability to distinguish between untrustworthy and credible users.

A Universal Model for Cross Modality Mapping by Relational Reasoning

no code implementations26 Feb 2021 Zun Li, Congyan Lang, Liqian Liang, Tao Wang, Songhe Feng, Jun Wu, Yidong Li

With the aim of matching a pair of instances from two different modalities, cross modality mapping has attracted growing attention in the computer vision community.

Image Classification Relational Reasoning

Robust Federated Learning for Neural Networks

no code implementations1 Jan 2021 Yao Zhou, Jun Wu, Jingrui He

In federated learning, data is distributed among local clients which collaboratively train a prediction model using secure aggregation.

Federated Learning

Continuous Transfer Learning

no code implementations1 Jan 2021 Jun Wu, Jingrui He

One major challenge associated with continuous transfer learning is the time evolving relatedness of the source domain and the current target domain as the target domain evolves over time.

Transfer Learning

Leveraging AI and Intelligent Reflecting Surface for Energy-Efficient Communication in 6G IoT

no code implementations29 Dec 2020 Qianqian Pan, Jun Wu, Xi Zheng, Jianhua Li, Shenghong Li, Athanasios V. Vasilakos

The ever-increasing data traffic, various delay-sensitive services, and the massive deployment of energy-limited Internet of Things (IoT) devices have brought huge challenges to the current communication networks, motivating academia and industry to move to the sixth-generation (6G) network.


GAN-based Recommendation with Positive-Unlabeled Sampling

no code implementations12 Dec 2020 Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Korpeoglu, Kannan Achan, Jingrui He

Recommender systems are popular tools for information retrieval tasks on a large variety of web applications and personalized products.

Information Retrieval Recommendation Systems +1

Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning

1 code implementation18 Sep 2020 Yao Zhou, Jun Wu, Haixun Wang, Jingrui He

In this work, we show that this paradigm might inherit the adversarial vulnerability of the centralized neural network, i. e., it has deteriorated performance on adversarial examples when the model is deployed.

Adversarial Robustness Federated Learning +1

Structure Learning for Cyclic Linear Causal Models

no code implementations10 Jun 2020 Carlos Améndola, Philipp Dettling, Mathias Drton, Federica Onori, Jun Wu

We consider the problem of structure learning for linear causal models based on observational data.

Continuous Transfer Learning with Label-informed Distribution Alignment

no code implementations5 Jun 2020 Jun Wu, Jingrui He

To bridge this gap, in this paper, we study a novel continuous transfer learning setting with a time evolving target domain.

Transfer Learning

A framework for adaptive width control of dense contour-parallel toolpaths in fused deposition modeling

2 code implementations28 Apr 2020 Tim Kuipers, Eugeni L. Doubrovski, Jun Wu, Charlie C. L. Wang

In this paper we present a framework which supports multiple schemes to generate toolpaths with adaptive width, by employing a function to decide the number of beads and their widths.

Graphics Robotics Systems and Control Systems and Control J.6

Fitting the Search Space of Weight-sharing NAS with Graph Convolutional Networks

no code implementations17 Apr 2020 Xin Chen, Lingxi Xie, Jun Wu, Longhui Wei, Yuhui Xu, Qi Tian

We alleviate this issue by training a graph convolutional network to fit the performance of sampled sub-networks so that the impact of random errors becomes minimal.

Neural Architecture Search

Progressive DARTS: Bridging the Optimization Gap for NAS in the Wild

2 code implementations23 Dec 2019 Xin Chen, Lingxi Xie, Jun Wu, Qi Tian

With the rapid development of neural architecture search (NAS), researchers found powerful network architectures for a wide range of vision tasks.

Neural Architecture Search

Robust Data Preprocessing for Machine-Learning-Based Disk Failure Prediction in Cloud Production Environments

no code implementations20 Dec 2019 Shujie Han, Jun Wu, Erci Xu, Cheng He, Patrick P. C. Lee, Yi Qiang, Qixing Zheng, Tao Huang, Zixi Huang, Rui Li

To provide proactive fault tolerance for modern cloud data centers, extensive studies have proposed machine learning (ML) approaches to predict imminent disk failures for early remedy and evaluated their approaches directly on public datasets (e. g., Backblaze SMART logs).

BIG-bench Machine Learning

Hierarchical Attention Networks for Medical Image Segmentation

no code implementations20 Nov 2019 Fei Ding, Gang Yang, Jinlu Liu, Jun Wu, Dayong Ding, Jie Xv, Gangwei Cheng, Xirong Li

Unlike previous self-attention based methods that capture context information from one level, we reformulate the self-attention mechanism from the view of the high-order graph and propose a novel method, namely Hierarchical Attention Network (HANet), to address the problem of medical image segmentation.

Image Segmentation Medical Image Segmentation +1

Progressive Differentiable Architecture Search: Bridging the Depth Gap between Search and Evaluation

4 code implementations ICCV 2019 Xin Chen, Lingxi Xie, Jun Wu, Qi Tian

Recently, differentiable search methods have made major progress in reducing the computational costs of neural architecture search.

Neural Architecture Search

Autoencoder Based Residual Deep Networks for Robust Regression Prediction and Spatiotemporal Estimation

no code implementations29 Dec 2018 Lianfa Li, Ying Fang, Jun Wu, Jinfeng Wang

To have a superior generalization, a deep learning neural network often involves a large size of training sample.

Imputation regression

ImVerde: Vertex-Diminished Random Walk for Learning Network Representation from Imbalanced Data

1 code implementation24 Apr 2018 Jun Wu, Jingrui He, Yongming Liu

Then, based on VDRW, we propose a semi-supervised network representation learning framework named ImVerde for imbalanced networks, in which context sampling uses VDRW and the label information to create node-context pairs, and balanced-batch sampling adopts a simple under-sampling method to balance these pairs in different classes.

Social and Information Networks

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