Search Results for author: Fan Liu

Found 40 papers, 11 papers with code

Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao Bound Optimization

no code implementations12 Jul 2022 Xianxin Song, Jie Xu, Fan Liu, Tony Xiao Han, Yonina C. Eldar

For the extended target case, we obtain the optimal transmit beamforming solution to minimize the CRB in closed form.

ISAC from the Sky: UAV Trajectory Design for Joint Communication and Target Localization

no code implementations6 Jul 2022 Xiaoye Jing, Fan Liu, Christos Masouros, Yong Zeng

In this paper, we consider an airborne integrated sensing and communications (ISAC) system where a UAV, which acts both as a communication BS and a mono-static radar, flies over a given area to transmit downlink signal to a ground communication user.

Prototypical Contrastive Language Image Pretraining

1 code implementation22 Jun 2022 Delong Chen, Zhao Wu, Fan Liu, Zaiquan Yang, Yixiang Huang, Yiping Bao, Erjin Zhou

In this paper, we show a representation grouping effect during this process: the InfoNCE objective indirectly groups semantically similar representations together via randomly emerged within-modal anchors.

Zero-Shot Learning

A Simple Baseline for Adversarial Domain Adaptation-based Unsupervised Flood Forecasting

no code implementations16 Jun 2022 Delong Chen, Ruizhi Zhou, Yanling Pan, Fan Liu

Specifically, training of FloodDAN includes two stages: in the first stage, we train a rainfall encoder and a prediction head to learn general transferable hydrological knowledge on large-scale source domain data; in the second stage, we transfer the knowledge in the pretrained encoder into the rainfall encoder of target domain through adversarial domain alignment.

Unsupervised Domain Adaptation

Cascading Residual Graph Convolutional Network for Multi-Behavior Recommendation

no code implementations26 May 2022 Mingshi Yan, Zhiyong Cheng, Chen Gao, Jing Sun, Fan Liu, Fuming Sun, Haojie Li

In particular, we design a cascading residual graph convolutional network structure, which enables our model to learn user preferences by continuously refining user embeddings across different types of behaviors.

Multi-Task Learning

Vehicular Connectivity on Complex Trajectories: Roadway-Geometry Aware ISAC Beam-tracking

no code implementations24 May 2022 Xiao Meng, Fan Liu, Christos Masouros, Weijie Yuan, Qixun Zhang, Zhiyong Feng

In this paper, we propose sensing-assisted beamforming designs for vehicles on arbitrarily shaped roads by relying on integrated sensing and communication (ISAC) signalling. Specifically, we aim to address the limitations of conventional ISAC beam-tracking schemes that do not apply to complex road geometries.

Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao Lower Bound Optimization

no code implementations23 Apr 2022 Xianxin Song, Jie Xu, Fan Liu, Tony Xiao Han, Yonina C. Eldar

Under this setup, we jointly design the transmit beamforming at the AP and the reflective beamforming at the IRS to minimize the DoA estimation error in terms of Cram\'er-Rao lower bound (CRLB).

Analysis Method of Strapdown Inertial Navigation Error Distribution Based on Covariance Matrix Decomposition

1 code implementation22 Mar 2022 Xiaokang Yang, Gongmin Yan, Fan Liu, Bofan Guan, Sihai Li

Compared with the Monte-Carlo method and other method based on covariance matrix, the proposed method uses more complete error model, considers the interaction effect of error sources and can be easily realized with less computation.

Disentangled Multimodal Representation Learning for Recommendation

no code implementations10 Mar 2022 Fan Liu, Zhiyong Cheng, Huilin Chen, AnAn Liu, Liqiang Nie, Mohan Kankanhalli

In particular, we adopt a disentangled representation technique to ensure the features of different factors in each modality are independent to each other.

Recommendation Systems Representation Learning

Sensing as A Service in 6G Perceptive Networks: A Unified Framework for ISAC Resource Allocation

no code implementations21 Feb 2022 Fuwang Dong, Fan Liu, Yuanhao Cui, Wei Wang, Kaifeng Han, Zhiqin Wang

Then, we establish a unified framework for ISAC resource allocation, where the fairness and the comprehensiveness optimization criteria are considered for the aforementioned sensing services.


An Experimental Proof of Concept for Integrated Sensing and Communications Waveform Design

no code implementations9 Feb 2022 Tongyang Xu, Fan Liu, Christos Masouros, Izzat Darwazeh

This experimental work focuses on a dual-functional radar sensing and communication framework where a single radiation waveform, either omnidirectional or directional, can realize both radar sensing and communication functions.

Disentangled Graph Neural Networks for Session-based Recommendation

no code implementations10 Jan 2022 Ansong Li, Zhiyong Cheng, Fan Liu, Zan Gao, Weili Guan, Yuxin Peng

The session embedding is then generated by aggregating the item embeddings with attention weights of each item's factors.

Session-Based Recommendations

MIMO-OFDM Dual-Functional Radar-Communication Systems: Low-PAPR Waveform Design

no code implementations27 Sep 2021 Xiaoyan Hu, Christos Masouros, Fan Liu, Ronald Nissel

In this paper, we explore a dual-functional radar-communication (DFRC) system for achieving integrated sensing and communications (ISAC).

VirtualConductor: Music-driven Conducting Video Generation System

no code implementations28 Jul 2021 Delong Chen, Fan Liu, Zewen Li, Feng Xu

In this demo, we present VirtualConductor, a system that can generate conducting video from any given music and a single user's image.

Pose Transfer Video Generation

Accelerating Edge Intelligence via Integrated Sensing and Communication

no code implementations20 Jul 2021 Tong Zhang, Shuai Wang, Guoliang Li, Fan Liu, Guangxu Zhu, Rui Wang

Conventionally, the sensing and communication stages are executed sequentially, which results in excessive amount of dataset generation and uploading time.

Significant Wave Height Prediction based on Wavelet Graph Neural Network

no code implementations20 Jul 2021 Delong Chen, Fan Liu, Zheqi Zhang, Xiaomin Lu, Zewen Li

Several parallel graph neural networks are separately trained on wavelet decomposed data, and the reconstruction of each model's prediction forms the final SWH prediction.

BIG-bench Machine Learning

Rethinking the Tradeoff in Integrated Sensing and Communication: Recognition Accuracy versus Communication Rate

no code implementations20 Jul 2021 Guoliang Li, Shuai Wang, Jie Li, Rui Wang, Fan Liu, Meihong Zhang, Xiaohui Peng, Tony Xiao Han

Integrated sensing and communication (ISAC) is a promising technology to improve the band-utilization efficiency via spectrum sharing or hardware sharing between radar and communication systems.

Towards Multi-Functional 6G Wireless Networks: Integrating Sensing, Communication and Security

no code implementations16 Jul 2021 Zhongxiang Wei, Fan Liu, Christos Masouros, Nanchi Su, Athina P. Petropulu

At the same time, the sensing capability incorporated in the ISAC transmission offers unique opportunities to design secure ISAC techniques.

Secure Dual-Functional Radar-Communication Transmission: Exploiting Interference for Resilience Against Target Eavesdropping

no code implementations10 Jul 2021 Nanchi Su, Fan Liu, Zhongxiang Wei, Ya-Feng Liu, Christos Masouros

We study security solutions for dual-functional radar communication (DFRC) systems, which detect the radar target and communicate with downlink cellular users in millimeter-wave (mmWave) wireless networks simultaneously.

Long-term Cross Adversarial Training: A Robust Meta-learning Method for Few-shot Classification Tasks

1 code implementation ICML Workshop AML 2021 Fan Liu, Shuyu Zhao, Xuelong Dai, Bin Xiao

Although adversarial training (AT) methods such as Adversarial Query (AQ) can improve the adversarially robust performance of meta-learning models, AT is still computationally expensive training.

Adversarial Robustness Classification +1

Integrating Sensing and Communications for Ubiquitous IoT: Applications, Trends and Challenges

no code implementations23 Apr 2021 Yuanhao Cui, Fan Liu, Xiaojun Jing, Junsheng Mu

Meanwhile, triggered by ISAC, we are also witnessing a paradigm shift in the ubiquitous IoT architecture, in which the sensing and communication layers are tending to converge into a new layer, namely, the signaling layer.

Hardware Efficient Joint Radar-Communications with Hybrid Precoding and RF Chain Optimization

no code implementations16 Apr 2021 Aryan Kaushik, Christos Masouros, Fan Liu

In this paper, we aim to achieve energy efficient design with minimum hardware requirement for hybrid precoding, which enables a large number of antennas with minimal number of RF chains, and sub-arrayed multiple-input multiple-output (MIMO) radar based joint radar-communication (JRC) systems.

An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing

1 code implementation25 Feb 2021 J. Andrew Zhang, Fan Liu, Christos Masouros, Robert W. Heath Jr., Zhiyong Feng, Le Zheng, Athina Petropulu

Joint communication and radar sensing (JCR) represents an emerging research field aiming to integrate the above two functionalities into a single system, sharing a majority of hardware and signal processing modules and, in a typical case, sharing a single transmitted signal.

Feature-level Attentive ICF for Recommendation

1 code implementation22 Feb 2021 Zhiyong Cheng, Fan Liu, Shenghan Mei, Yangyang Guo, Lei Zhu, Liqiang Nie

To demonstrate the effectiveness of our method, we design a light attention neural network to integrate both item-level and feature-level attention for neural ICF models.

Collaborative Filtering Recommendation Systems

Interest-aware Message-Passing GCN for Recommendation

1 code implementation19 Feb 2021 Fan Liu, Zhiyong Cheng, Lei Zhu, Zan Gao, Liqiang Nie

To form the subgraphs, we design an unsupervised subgraph generation module, which can effectively identify users with common interests by exploiting both user feature and graph structure.

Cramér-Rao Bound Optimization for Joint Radar-Communication Design

no code implementations29 Jan 2021 Fan Liu, Ya-Feng Liu, Ang Li, Christos Masouros, Yonina C. Eldar

We employ the Cram\'er-Rao bound (CRB) as a performance metric of target estimation, under both point and extended target scenarios.

Learning to Select for MIMO Radar based on Hybrid Analog-Digital Beamforming

no code implementations18 Jan 2021 Zhaoyi Xu, Fan Liu, Konstantinos Diamantaras, Christos Masouros, Athina Petropulu

In this paper, we propose an energy-efficient radar beampattern design framework for a Millimeter Wave (mmWave) massive multi-input multi-output (mMIMO) system, equipped with a hybrid analog-digital (HAD) beamforming structure.

BIG-bench Machine Learning

Deep Learning Based Single Sample Per Person Face Recognition: A Survey

no code implementations9 Jun 2020 Fan Liu, Delong Chen, Fei Wang, Zewen Li, Feng Xu

Face recognition under this situation is referred to as single sample face recognition and poses significant challenges to the effective training of deep models.

Domain Adaptation Face Recognition

A Review of Automated Diagnosis of COVID-19 Based on Scanning Images

no code implementations9 Jun 2020 Delong Chen, Shunhui Ji, Fan Liu, Zewen Li, Xinyu Zhou

The pandemic of COVID-19 has caused millions of infections, which has led to a great loss all over the world, socially and economically.

Computed Tomography (CT) Domain Adaptation

Bayesian Predictive Beamforming for Vehicular Networks: A Low-overhead Joint Radar-Communication Approach

no code implementations15 May 2020 Weijie Yuan, Fan Liu, Christos Masouros, Jinhong Yuan, Derrick Wing Kwan Ng, Nuria Gonzalez-Prelcic

To accurately estimate the motion parameters of vehicles in real-time, we propose a novel message passing algorithm based on factor graph, which yields near optimal solution to the maximum a posteriori estimation.

A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects

no code implementations1 Apr 2020 Zewen Li, Wenjie Yang, Shouheng Peng, Fan Liu

In this review, we aim to provide novel ideas and prospects in this fast-growing field as much as possible.

Natural Language Processing

A^2-GCN: An Attribute-aware Attentive GCN Model for Recommendation

no code implementations20 Mar 2020 Fan Liu, Zhiyong Cheng, Lei Zhu, Chenghao Liu, Liqiang Nie

Considering the fact that for different users, the attributes of an item have different influence on their preference for this item, we design a novel attention mechanism to filter the message passed from an item to a target user by considering the attribute information.

Recommendation Systems

User Diverse Preference Modeling by Multimodal Attentive Metric Learning

1 code implementation21 Aug 2019 Fan Liu, Zhiyong Cheng, Changchang Sun, Yinglong Wang, Liqiang Nie, Mohan Kankanhalli

To tackle this problem, in this paper, we propose a novel Multimodal Attentive Metric Learning (MAML) method to model user diverse preferences for various items.

Metric Learning Recommendation Systems

Truncated nuclear norm regularization for low-rank tensor completion

1 code implementation7 Jan 2019 Shengke Xue, Wenyuan Qiu, Fan Liu, Xinyu Jin

It is proved that the recently proposed truncated nuclear norm (TNN) can replace the traditional nuclear norm, as an improved approximation to the rank of a matrix.

Low-Rank Tensor Completion by Truncated Nuclear Norm Regularization

1 code implementation3 Dec 2017 Shengke Xue, Wenyuan Qiu, Fan Liu, Xinyu Jin

Currently, low-rank tensor completion has gained cumulative attention in recovering incomplete visual data whose partial elements are missing.

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