Search Results for author: Shuguang Cui

Found 74 papers, 17 papers with code

Multi-level Consistency Learning for Semi-supervised Domain Adaptation

no code implementations9 May 2022 Zizheng Yan, Yushuang Wu, Guanbin Li, Yipeng Qin, Xiaoguang Han, Shuguang Cui

Semi-supervised domain adaptation (SSDA) aims to apply knowledge learned from a fully labeled source domain to a scarcely labeled target domain.

Domain Adaptation

DArch: Dental Arch Prior-assisted 3D Tooth Instance Segmentation

no code implementations25 Apr 2022 Liangdong Qiu, Chongjie Ye, Pei Chen, Yunbi Liu, Xiaoguang Han, Shuguang Cui

Experimental results on $4, 773$ dental models have shown our DArch can accurately segment each tooth of a dental model, and its performance is superior to the state-of-the-art methods.

Instance Segmentation Semantic Segmentation

PointMatch: A Consistency Training Framework for Weakly SupervisedSemantic Segmentation of 3D Point Clouds

no code implementations22 Feb 2022 Yushuang Wu, Zizheng Yan, Shengcai Cai, Guanbin Li, Yizhou Yu, Xiaoguang Han, Shuguang Cui

Semantic segmentation of point cloud usually relies on dense annotation that is exhausting and costly, so it attracts wide attention to investigate solutions for the weakly supervised scheme with only sparse points annotated.

Representation Learning Semantic Segmentation

Vertical Federated Edge Learning with Distributed Integrated Sensing and Communication

no code implementations21 Jan 2022 Peixi Liu, Guangxu Zhu, Wei Jiang, Wu Luo, Jie Xu, Shuguang Cui

This letter studies a vertical federated edge learning (FEEL) system for collaborative objects/human motion recognition by exploiting the distributed integrated sensing and communication (ISAC).

Federated Two-stage Learning with Sign-based Voting

no code implementations10 Dec 2021 Zichen Ma, Zihan Lu, Yu Lu, Wenye Li, JinFeng Yi, Shuguang Cui

In this paper, we design a federated two-stage learning framework that augments prototypical federated learning with a cut layer on devices and uses sign-based stochastic gradient descent with the majority vote method on model updates.

Federated Learning

Joint LED Selection and Precoding Optimization for Multiple-User Multiple-Cell VLC Systems

no code implementations29 Aug 2021 Yang Yang, Yujie Yang, Mingzhe Chen, Chunyan Feng, Hailun Xia, Shuguang Cui, H. Vincent Poor

First, a MU-MC-VLC system model is established, and then a sum-rate maximization problem under dimming level and illumination uniformity constraints is formulated.

Device-Free Sensing in OFDM Cellular Network

no code implementations20 Aug 2021 Qin Shi, Liang Liu, Shuowen Zhang, Shuguang Cui

A novel two-phase sensing framework is proposed to localize the passive targets that cannot transmit/receive reference signals to/from the base stations (BSs), where the ranges of the targets are estimated based on their reflected OFDM signals to the BSs in Phase I, and the location of each target is estimated based on its ranges to different BSs in Phase II.

Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds

2 code implementations ICCV 2021 Chaoda Zheng, Xu Yan, Jiantao Gao, Weibing Zhao, Wei zhang, Zhen Li, Shuguang Cui

Current 3D single object tracking approaches track the target based on a feature comparison between the target template and the search area.

Frame Object Tracking

Colorectal Polyp Classification from White-light Colonoscopy Images via Domain Alignment

no code implementations5 Aug 2021 Qin Wang, Hui Che, Weizhen Ding, Li Xiang, Guanbin Li, Zhen Li, Shuguang Cui

Thus, we propose a novel framework based on a teacher-student architecture for the accurate colorectal polyp classification (CPC) through directly using white-light (WL) colonoscopy images in the examination.

Contrastive Learning

Shallow Feature Matters for Weakly Supervised Object Localization

1 code implementation CVPR 2021 Jun Wei, Qin Wang, Zhen Li, Sheng Wang, S. Kevin Zhou, Shuguang Cui

In practice, our SPOL model first generates the CAMs through a novel element-wise multiplication of shallow and deep feature maps, which filters the background noise and generates sharper boundaries robustly.

Weakly-Supervised Object Localization

Shallow Attention Network for Polyp Segmentation

1 code implementation2 Aug 2021 Jun Wei, Yiwen Hu, Ruimao Zhang, Zhen Li, S. Kevin Zhou, Shuguang Cui

To address the above issues, we propose the Shallow Attention Network (SANet) for polyp segmentation.

Video Polyp Segmentation

Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling

no code implementations24 Jul 2021 Maojun Zhang, Guangxu Zhu, Shuai Wang, Jiamo Jiang, Caijun Zhong, Shuguang Cui

Building on the analytical result, an optimized probabilistic scheduling policy is derived in closed-form by solving the approximate communication time minimization problem.

Autonomous Driving Learning Theory

From Single to Multiple: Leveraging Multi-level Prediction Spaces for Video Forecasting

no code implementations21 Jul 2021 Mengcheng Lan, Shuliang Ning, Yanran Li, Qian Chen, Xunlai Chen, Xiaoguang Han, Shuguang Cui

Despite video forecasting has been a widely explored topic in recent years, the mainstream of the existing work still limits their models with a single prediction space but completely neglects the way to leverage their model with multi-prediction spaces.

Video Prediction

Task-Aware Sampling Layer for Point-Wise Analysis

no code implementations9 Jul 2021 Yiqun Lin, Lichang Chen, Haibin Huang, Chongyang Ma, Xiaoguang Han, Shuguang Cui

Sampling, grouping, and aggregation are three important components in the multi-scale analysis of point clouds.

Keypoint Detection Point Cloud Completion

Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation

1 code implementation29 Jun 2021 Guangyi Liu, Zichao Yang, Tianhua Tao, Xiaodan Liang, Junwei Bao, Zhen Li, Xiaodong He, Shuguang Cui, Zhiting Hu

Such training objective is sub-optimal when the target sequence is not perfect, e. g., when the target sequence is corrupted with noises, or when only weak sequence supervision is available.

Machine Translation Style Transfer +3

Towards Heterogeneous Clients with Elastic Federated Learning

no code implementations17 Jun 2021 Zichen Ma, Yu Lu, Zihan Lu, Wenye Li, JinFeng Yi, Shuguang Cui

Training in heterogeneous and potentially massive networks introduces bias into the system, which is originated from the non-IID data and the low participation rate in reality.

Federated Learning

RevCore: Review-augmented Conversational Recommendation

no code implementations Findings (ACL) 2021 Yu Lu, Junwei Bao, Yan Song, Zichen Ma, Shuguang Cui, Youzheng Wu, Xiaodong He

Existing conversational recommendation (CR) systems usually suffer from insufficient item information when conducted on short dialogue history and unfamiliar items.

Response Generation

PointLIE: Locally Invertible Embedding for Point Cloud Sampling and Recovery

1 code implementation30 Apr 2021 Weibing Zhao, Xu Yan, Jiantao Gao, Ruimao Zhang, Jiayan Zhang, Zhen Li, Song Wu, Shuguang Cui

In this paper, we address a fundamental problem in PCSR: How to downsample the dense point cloud with arbitrary scales while preserving the local topology of discarding points in a case-agnostic manner (i. e. without additional storage for point relationship)?

Distributed Reinforcement Learning for Age of Information Minimization in Real-Time IoT Systems

no code implementations4 Apr 2021 Sihua Wang, Mingzhe Chen, Zhaohui Yang, Changchuan Yin, Walid Saad, Shuguang Cui, H. Vincent Poor

In this paper, the problem of minimizing the weighted sum of age of information (AoI) and total energy consumption of Internet of Things (IoT) devices is studied.

reinforcement-learning Total Energy

Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey

no code implementations18 Mar 2021 Kai Chen, Qinglei Kong, Yijue Dai, Yue Xu, Feng Yin, Lexi Xu, Shuguang Cui

Empowered by big data and machine learning, next-generation data-driven communication systems will be intelligent with the characteristics of expressiveness, scalability, interpretability, and especially uncertainty modeling, which can confidently involve diversified latent demands and personalized services in the foreseeable future.

Gaussian Processes

Optimization of User Selection and Bandwidth Allocation for Federated Learning in VLC/RF Systems

no code implementations5 Mar 2021 Chuanhong Liu, Caili Guo, Yang Yang, Mingzhe Chen, H. Vincent Poor, Shuguang Cui

Then, the problem of user selection and bandwidth allocation is studied for FL implemented over a hybrid VLC/RF system aiming to optimize the FL performance.

Federated Learning

Meta-Reinforcement Learning for Reliable Communication in THz/VLC Wireless VR Networks

1 code implementation29 Jan 2021 Yining Wang, Mingzhe Chen, Zhaohui Yang, Walid Saad, Tao Luo, Shuguang Cui, H. Vincent Poor

The problem is formulated as an optimization problem whose goal is to maximize the reliability of the VR network by selecting the appropriate VAPs to be turned on and controlling the user association with SBSs.

Meta-Learning Meta Reinforcement Learning +1

A Comprehensive Survey on 6G Networks:Applications, Core Services, Enabling Technologies, and Future Challenges

no code implementations29 Jan 2021 Amin Shahraki, Mahmoud Abbasi, Md. Jalil Piran, Mingzhe Chen, Shuguang Cui

Cellular Internet of Things (IoT) is considered as de facto paradigm to improve the communication and computation systems.

Networking and Internet Architecture

LapsCore: Language-Guided Person Search via Color Reasoning

no code implementations ICCV 2021 Yushuang Wu, Zizheng Yan, Xiaoguang Han, Guanbin Li, Changqing Zou, Shuguang Cui

The key point of language-guided person search is to construct the cross-modal association between visual and textual input.

Colorization Person Search +1

Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion

1 code implementation7 Dec 2020 Xu Yan, Jiantao Gao, Jie Li, Ruimao Zhang, Zhen Li, Rui Huang, Shuguang Cui

In practice, an initial semantic segmentation (SS) of a single sweep point cloud can be achieved by any appealing network and then flows into the semantic scene completion (SSC) module as the input.

3D Semantic Scene Completion from a single RGB image Autonomous Driving +2

Distributed Multi-agent Meta Learning for Trajectory Design in Wireless Drone Networks

no code implementations6 Dec 2020 Ye Hu, Mingzhe Chen, Walid Saad, H. Vincent Poor, Shuguang Cui

Analytical results show that, the proposed VD-RL algorithm is guaranteed to converge to a local optimal solution of the non-convex optimization problem.


On the Adversarial Robustness of LASSO Based Feature Selection

no code implementations20 Oct 2020 Fuwei Li, Lifeng Lai, Shuguang Cui

We formulate the modification strategy of the adversary as a bi-level optimization problem.

Adversarial Robustness

A Machine Learning Approach for Task and Resource Allocation in Mobile Edge Computing Based Networks

no code implementations20 Jul 2020 Sihua Wang, Mingzhe Chen, Xuanlin Liu, Changchuan Yin, Shuguang Cui, H. Vincent Poor

Since the data size of each computational task is different, as the requested computational task varies, the BSs must adjust their resource (subcarrier and transmit power) and task allocation schemes to effectively serve the users.

Edge-computing Q-Learning

Delay Minimization for Federated Learning Over Wireless Communication Networks

no code implementations5 Jul 2020 Zhaohui Yang, Mingzhe Chen, Walid Saad, Choong Seon Hong, Mohammad Shikh-Bahaei, H. Vincent Poor, Shuguang Cui

In this paper, the problem of delay minimization for federated learning (FL) over wireless communication networks is investigated.

Federated Learning

From Spectrum Wavelet to Vertex Propagation: Graph Convolutional Networks Based on Taylor Approximation

no code implementations1 Jul 2020 Songyang Zhang, Han Zhang, Shuguang Cui, Zhi Ding

Graph convolutional networks (GCN) have been recently utilized to extract the underlying structures of datasets with some labeled data and high-dimensional features.

Node Classification

UVeQFed: Universal Vector Quantization for Federated Learning

1 code implementation5 Jun 2020 Nir Shlezinger, Mingzhe Chen, Yonina C. Eldar, H. Vincent Poor, Shuguang Cui

We show that combining universal vector quantization methods with FL yields a decentralized training system in which the compression of the trained models induces only a minimum distortion.

Federated Learning Quantization

Wireless Communications for Collaborative Federated Learning

no code implementations3 Jun 2020 Mingzhe Chen, H. Vincent Poor, Walid Saad, Shuguang Cui

However, due to resource constraints and privacy challenges, edge IoT devices may not be able to transmit their collected data to a central controller for training machine learning models.

Federated Learning

Meta-Reinforcement Learning for Trajectory Design in Wireless UAV Networks

no code implementations25 May 2020 Ye Hu, Mingzhe Chen, Walid Saad, H. Vincent Poor, Shuguang Cui

Meanwhile, the probability that the DBS serves over 50% of user requests increases about 27%, compared to the baseline policy gradient algorithm.

Meta-Learning Meta Reinforcement Learning +1

Energy-Efficient Wireless Communications with Distributed Reconfigurable Intelligent Surfaces

no code implementations1 May 2020 Zhaohui Yang, Mingzhe Chen, Walid Saad, Wei Xu, Mohammad Shikh-Bahaei, H. Vincent Poor, Shuguang Cui

In this network, multiple RISs are spatially distributed to serve wireless users and the energy efficiency of the network is maximized by dynamically controlling the on-off status of each RIS as well as optimizing the reflection coefficients matrix of the RISs.

Deep Fashion3D: A Dataset and Benchmark for 3D Garment Reconstruction from Single Images

2 code implementations ECCV 2020 Heming Zhu, Yu Cao, Hang Jin, Weikai Chen, Dong Du, Zhangye Wang, Shuguang Cui, Xiaoguang Han

High-fidelity clothing reconstruction is the key to achieving photorealism in a wide range of applications including human digitization, virtual try-on, etc.

Virtual Try-on

Peeking into occluded joints: A novel framework for crowd pose estimation

1 code implementation ECCV 2020 Lingteng Qiu, Xuanye Zhang, Yan-ran Li, Guanbin Li, Xiao-Jun Wu, Zixiang Xiong, Xiaoguang Han, Shuguang Cui

Although occlusion widely exists in nature and remains a fundamental challenge for pose estimation, existing heatmap-based approaches suffer serious degradation on occlusions.

Pose Estimation

Federated Learning for Task and Resource Allocation in Wireless High Altitude Balloon Networks

no code implementations19 Mar 2020 Sihua Wang, Mingzhe Chen, Changchuan Yin, Walid Saad, Choong Seon Hong, Shuguang Cui, H. Vincent Poor

This problem is posed as an optimization problem whose goal is to minimize the energy and time consumption for task computing and transmission by adjusting the user association, service sequence, and task allocation scheme.

Edge-computing Federated Learning

PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling

1 code implementation CVPR 2020 Xu Yan, Chaoda Zheng, Zhen Li, Sheng Wang, Shuguang Cui

Extensive experiments verify the robustness and superiority of our approach in point clouds processing tasks regardless of synthesis data, indoor data, and outdoor data with or without noise.

Scalable Learning Paradigms for Data-Driven Wireless Communication

no code implementations1 Mar 2020 Yue Xu, Feng Yin, Wenjun Xu, Chia-Han Lee, Jia-Ru Lin, Shuguang Cui

The marriage of wireless big data and machine learning techniques revolutionizes the wireless system by the data-driven philosophy.

Optimal Feature Manipulation Attacks Against Linear Regression

no code implementations29 Feb 2020 Fuwei Li, Lifeng Lai, Shuguang Cui

In this paper, we investigate how to manipulate the coefficients obtained via linear regression by adding carefully designed poisoning data points to the dataset or modify the original data points.

Artificial Intelligence Aided Next-Generation Networks Relying on UAVs

no code implementations28 Jan 2020 Xiao Liu, Mingzhe Chen, Yuanwei Liu, Yue Chen, Shuguang Cui, Lajos Hanzo

Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aided next-generation networking is proposed for dynamic environments.

Convergence Time Optimization for Federated Learning over Wireless Networks

no code implementations22 Jan 2020 Mingzhe Chen, H. Vincent Poor, Walid Saad, Shuguang Cui

Due to the limited number of resource blocks (RBs) in a wireless network, only a subset of users can be selected to transmit their local FL model parameters to the BS at each learning step.

Federated Learning

Point Cloud Segmentation based on Hypergraph Spectral Clustering

no code implementations21 Jan 2020 Songyang Zhang, Shuguang Cui, Zhi Ding

Hypergraph spectral analysis has emerged as an effective tool processing complex data structures in data analysis.

Point Cloud Segmentation

Hypergraph Spectral Analysis and Processing in 3D Point Cloud

no code implementations8 Jan 2020 Songyang Zhang, Shuguang Cui, Zhi Ding

Along with increasingly popular virtual reality applications, the three-dimensional (3D) point cloud has become a fundamental data structure to characterize 3D objects and surroundings.


A Joint Learning and Communications Framework for Federated Learning over Wireless Networks

1 code implementation17 Sep 2019 Mingzhe Chen, Zhaohui Yang, Walid Saad, Changchuan Yin, H. Vincent Poor, Shuguang Cui

This joint learning, wireless resource allocation, and user selection problem is formulated as an optimization problem whose goal is to minimize an FL loss function that captures the performance of the FL algorithm.

Federated Learning

On the Adversarial Robustness of Subspace Learning

no code implementations17 Aug 2019 Fuwei Li, Lifeng Lai, Shuguang Cui

We first characterize the optimal rank-one attack strategy that maximizes the subspace distance between the subspace learned from the original data matrix and that learned from the modified data matrix.

Adversarial Robustness

Introducing Hypergraph Signal Processing: Theoretical Foundation and Practical Applications

no code implementations22 Jul 2019 Songyang Zhang, Zhi Ding, Shuguang Cui

Signal processing over graphs has recently attracted significant attentions for dealing with structured data.

Voting-Based Multi-Agent Reinforcement Learning for Intelligent IoT

no code implementations2 Jul 2019 Yue Xu, Zengde Deng, Mengdi Wang, Wenjun Xu, Anthony Man-Cho So, Shuguang Cui

The recent success of single-agent reinforcement learning (RL) in Internet of things (IoT) systems motivates the study of multi-agent reinforcement learning (MARL), which is more challenging but more useful in large-scale IoT.

Decision Making Multi-agent Reinforcement Learning +1

Load Balancing for Ultra-Dense Networks: A Deep Reinforcement Learning Based Approach

no code implementations3 Jun 2019 Yue Xu, Wenjun Xu, Zhi Wang, Jia-Ru Lin, Shuguang Cui

Third, this work proposes an offline-evaluation based safeguard mechanism to ensure that the online system can always operate with the optimal and well-trained MLB policy, which not only stabilizes the online performance but also enables the exploration beyond current policies to make full use of machine learning in a safe way.


Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image

no code implementations CVPR 2019 Xiaoguang Han, Zhaoxuan Zhang, Dong Du, Mingdai Yang, Jingming Yu, Pan Pan, Xin Yang, Ligang Liu, Zixiang Xiong, Shuguang Cui

Given a single depth image, our method first goes through the 3D volume branch to obtain a volumetric scene reconstruction as a guide to the next view inpainting step, which attempts to make up the missing information; the third step involves projecting the volume under the same view of the input, concatenating them to complete the current view depth, and integrating all depth into the point cloud.

Wireless Traffic Prediction with Scalable Gaussian Process: Framework, Algorithms, and Verification

no code implementations13 Feb 2019 Yue Xu, Feng Yin, Wenjun Xu, Jia-Ru Lin, Shuguang Cui

First, to the best of our knowledge, this paper is the first to empower GP regression with the alternating direction method of multipliers (ADMM) for parallel hyper-parameter optimization in the training phase, where such a scalable training framework well balances the local estimation in baseband units (BBUs) and information consensus among BBUs in a principled way for large-scale executions.

Traffic Prediction

Learning Mutually Local-global U-nets For High-resolution Retinal Lesion Segmentation in Fundus Images

no code implementations18 Jan 2019 Zizheng Yan, Xiaoguang Han, Changmiao Wang, Yuda Qiu, Zixiang Xiong, Shuguang Cui

Due to high-resolution and small-size lesion regions, applying existing methods, such as U-Nets, to perform segmentation on fundus photography is very challenging.

Lesion Segmentation

Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine

no code implementations26 Dec 2018 Han Zhang, Bo Ai, Wenjun Xu, Li Xu, Shuguang Cui

Channel interpolation is an essential technique for providing high-accuracy estimation of the channel state information (CSI) for wireless systems design where the frequency-space structural correlations of multi-antenna channel are typically hidden in matrix or tensor forms.

A Two-Step Learning and Interpolation Method for Location-Based Channel Database

no code implementations4 Dec 2018 Ruichen Deng, Zhiyuan Jiang, Sheng Zhou, Shuguang Cui, Zhisheng Niu

Timely and accurate knowledge of channel state information (CSI) is necessary to support scheduling operations at both physical and network layers.

Fast Similarity Search via Optimal Sparse Lifting

no code implementations NeurIPS 2018 Wenye Li, Jingwei Mao, Yin Zhang, Shuguang Cui

Similarity search is a fundamental problem in computing science with various applications and has attracted significant research attention, especially in large-scale search with high dimensions.

CaricatureShop: Personalized and Photorealistic Caricature Sketching

no code implementations24 Jul 2018 Xiaoguang Han, Kangcheng Hou, Dong Du, Yuda Qiu, Yizhou Yu, Kun Zhou, Shuguang Cui

To construct the mapping between 2D sketches and a vertex-wise scaling field, a novel deep learning architecture is developed.

Caricature Face Model

Detection of Cooperative Interactions in Logistic Regression Models

no code implementations12 Feb 2016 Easton Li Xu, Xiaoning Qian, Tie Liu, Shuguang Cui

For the case when the underlying interaction graph is known to be acyclic, it is shown that a simple algorithm that is based on a maximum-weight spanning tree with respect to the plug-in estimates of the influences not only has strong theoretical performance guarantees, but can also outperform generic feature selection algorithms for recovering the interaction graph from i. i. d.

Cognitive Learning of Statistical Primary Patterns via Bayesian Network

no code implementations28 Sep 2014 Weijia Han, Huiyan Sang, Min Sheng, Jiandong Li, Shuguang Cui

How to learn such a BN structure is a long standing issue, not fully understood even in the statistical learning community.

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