91 citations · 251 across the 24 of their papers we have counts for
24 papers
Capacity and Delay of Unmanned Aerial Vehicle Networks with Mobility
Zhiqing Wei, Zhiyong Feng, Haibo Zhou +2
Unmanned aerial vehicles (UAVs) are widely exploited in environment monitoring, search-and-rescue, etc. However, the mobility and short flight duration of UAVs bring challenges for…
Progressive Dual Priori Network for Generalized Breast Tumor Segmentation
Li Wang, Lihui Wang, Zixiang Kuai +4
To promote the generalization ability of breast tumor segmentation models, as well as to improve the segmentation performance for breast tumors with smaller size, low-contrast and…
Differential-Equation Constrained Optimization With Stochasticity
Qin Li, Li Wang, Yunan Yang
Most inverse problems from physical sciences are formulated as PDE-constrained optimization problems. This involves identifying unknown parameters in equations by optimizing the mo…
BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation
Xiangyu Qin, Zhiyu Wu, Jinshi Cui +5
Previous works on emotion recognition in conversation (ERC) follow a two-step paradigm, which can be summarized as first producing context-independent features via fine-tuning pret…
MIMO Systems with Reconfigurable Antennas: Joint Channel Estimation and Mode Selection
Fariba Armandoust, Ehsan Tohidi, Martin Kasparick +3
Reconfigurable antennas (RAs) are a promising technology to enhance the capacity and coverage of wireless communication systems. However, RA systems have two major challenges: (i)…
Deep Factorization Model for Robust Recommendation
Li Wang, Qiang Zhao, Wei Wang
Recently, malevolent user hacking has become a huge problem for real-world companies. In order to learn predictive models for recommender systems, factorization techniques have bee…
Search for relativistic fractionally charged particles in space
DAMPE Collaboration, F. Alemanno, C. Altomare +148
More than a century after the performance of the oil drop experiment, the possible existence of fractionally charged particles FCP still remains unsettled. The search for FCPs is c…
Low Rank Tensor Decompositions and Approximations
Jiawang Nie, Li Wang, Zequn Zheng
There exist linear relations among tensor entries of low rank tensors. These linear relations can be expressed by multi-linear polynomials, which are called generating polynomials.…
Scalable and Sparsity-Aware Privacy-Preserving K-means Clustering with Application to Fraud Detection
Yingting Liu, Chaochao Chen, Jamie Cui +2
K-means is one of the most widely used clustering models in practice. Due to the problem of data isolation and the requirement for high model performance, how to jointly build prac…
Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation
Chaochao Chen, Huiwen Wu, Jiajie Su +3
Cross Domain Recommendation (CDR) has been popularly studied to alleviate the cold-start and data sparsity problem commonly existed in recommender systems. CDR models can improve t…
Exploiting Reconfigurable Intelligent Surfaces in Edge Caching: Joint Hybrid Beamforming and Content Placement Optimization
Yingyang Chen, Miaowen Wen, Ertugrul Basar +3
Edge caching can effectively reduce backhaul burden at core network and increase quality-ofservice at wireless edge nodes. However, the beneficial role of edge caching cannot be fu…
ASFGNN: Automated Separated-Federated Graph Neural Network
Longfei Zheng, Jun Zhou, Chaochao Chen +3
Graph Neural Networks (GNNs) have achieved remarkable performance by taking advantage of graph data. The success of GNN models always depends on rich features and adjacent relation…
Domain Adaptation Using Class Similarity for Robust Speech Recognition
Han Zhu, Jiangjiang Zhao, Yuling Ren +2
When only limited target domain data is available, domain adaptation could be used to promote performance of deep neural network (DNN) acoustic model by leveraging well-trained sou…
Orthogonal Multi-view Analysis by Successive Approximations via Eigenvectors
Li Wang, Leihong Zhang, Chungen Shen +1
We propose a unified framework for multi-view subspace learning to learn individual orthogonal projections for all views. The framework integrates the correlations within multiple…
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control
Chaochao Chen, Jun Zhou, Li Wang +7
Logistic Regression (LR) is the most widely used machine learning model in industry for its efficiency, robustness, and interpretability. Due to the problem of data isolation and t…
Multi-view Orthonormalized Partial Least Squares: Regularizations and Deep Extensions
Li Wang, Ren-Cang Li, Wen-Wei
We establish a family of subspace-based learning method for multi-view learning using the least squares as the fundamental basis. Specifically, we investigate orthonormalized parti…
A Lagrange Multiplier Expression Method for Bilevel Polynomial Optimization
Jiawang Nie, Li Wang, Jane Ye +1
This paper studies bilevel polynomial optimization problems. To solve them, we give a method based on polynomial optimization relaxations. Each relaxation is obtained from the Kura…
Deep Tensor CCA for Multi-view Learning
Hok Shing Wong, Li Wang, Raymond Chan +1
We present Deep Tensor Canonical Correlation Analysis (DTCCA), a method to learn complex nonlinear transformations of multiple views (more than two) of data such that the resulting…
Drosophila-Inspired 3D Moving Object Detection Based on Point Clouds
Li Wang, Dawei Zhao, Tao Wu +5
3D moving object detection is one of the most critical tasks in dynamic scene analysis. In this paper, we propose a novel Drosophila-inspired 3D moving object detection method usin…
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification
Chaochao Chen, Jun Zhou, Longfei Zheng +7
Recently, Graph Neural Network (GNN) has achieved remarkable progresses in various real-world tasks on graph data, consisting of node features and the adjacent information between…
Large-Scale Secure XGB for Vertical Federated Learning
Wenjing Fang, Derun Zhao, Jin Tan +6
Privacy-preserving machine learning has drawn increasingly attention recently, especially with kinds of privacy regulations come into force. Under such situation, Federated Learnin…
Privacy Preserving PCA for Multiparty Modeling
Yingting Liu, Chaochao Chen, Longfei Zheng +4
In this paper, we present a general multiparty modeling paradigm with Privacy Preserving Principal Component Analysis (PPPCA) for horizontally partitioned data. PPPCA can accomplis…
Large-Scale Semi-Supervised Learning via Graph Structure Learning over High-Dense Points
Zitong Wang, Li Wang, Raymond Chan +1
We focus on developing a novel scalable graph-based semi-supervised learning (SSL) method for a small number of labeled data and a large amount of unlabeled data. Due to the lack o…
Modeling Based on Elman Wavelet Neural Network for Class-D Power Amplifiers
Li Wang, Jie Shao, Yaqin Zhong +2
In Class-D Power Amplifiers (CDPAs), the power supply noise can intermodulate with the input signal, manifesting into power-supply induced intermodulation distortion (PS-IMD) and d…