Beilun Wang

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 39

Top Topics

Gaussian Graphical Models

Top Venues

Publications

Yutian Shi, Beilun Wang
A Privacy-Preserving Method for Sequential Recommendation in Vertical Federated Learning. CSCWD (2024)
Shidong Wang, Yangyang Shen, Fanwei Zeng, Meng Wang, Bohan Li, Dian Shen, Xiaodong Tang, Beilun Wang
Exploiting biochemical data to improve osteosarcoma diagnosis with deep learning. Health Inf. Sci. Syst. 12 (1) (2024)
Yuchen Wang, Jinghui Zhang, Zhengjie Huang, Weibin Li, Shikun Feng, Ziheng Ma, Yu Sun, Dianhai Yu, Fang Dong, Jiahui Jin, Beilun Wang, Junzhou Luo
Label Information Enhanced Fraud Detection against Low Homophily in Graphs. CoRR (2023)
Yuzhang Wu, Beilun Wang
A Framework Using Absolute Compression Hard-Threshold for Improving The Robustness of Federated Learning Model. CSCWD (2023)
Yuchen Wang, Jinghui Zhang, Zhengjie Huang, Weibin Li, Shikun Feng, Ziheng Ma, Yu Sun, Dianhai Yu, Fang Dong, Jiahui Jin, Beilun Wang, Junzhou Luo
Label Information Enhanced Fraud Detection against Low Homophily in Graphs. WWW (2023)
Yueyao Chen, Beilun Wang, Yan Zhang, Jingyu Kuang
A Robust Framework for Fixing The Vulnerability of Compressed Distributed Learning. CSCWD (2023)
Yan Zhang, Cheng Chen, Dian Shen, Meng Wang, Beilun Wang
Take CARE: Improving Inherent Robustness of Spiking Neural Networks with Channel-wise Activation Recalibration Module. ICDM (2023)
Xiao Tan, Yangyang Shen, Meng Wang, Beilun Wang
Graph Inference via the Energy-efficient Dynamic Precision Matrix Estimation with One-bit Data. CIKM (2023)
Ying Zhan, Beilun Wang
Collaborative Estimating Multiple Gaussian Graphical Models on Resource Constrained Devices in IoT Networks. SMC (2023)
Yueyao Chen, Beilun Wang, Tianyi Ma, Cheng Chen
Applying Robust Gradient Difference Compression to Federated Learning. CSCWD (2023)
Beilun Wang, Haoqing Xu, Chunshu Li, Yuchen Li, Meng Wang
TKGAT: Graph attention network for knowledge-enhanced tag-aware recommendation system. Knowl. Based Syst. 257 (2022)
Beilun Wang, Jiaqi Zhang, Haoqing Xu, Te Tao
Fast and scalable learning of sparse changes in high-dimensional graphical model structure. Neurocomputing 514 (2022)
Haoqing Xu, Meng Wang, Beilun Wang
A Difference Standardization Method for Mutual Transfer Learning. ICML (2022)
Kaihong Huang, Chunshu Li, Jiaqi Zhang, Beilun Wang
Cascade and Fusion: A Deep Learning Approach for Camouflaged Object Sensing. Sensors 21 (16) (2021)
Beilun Wang, Jiaqi Zhang, Yan Zhang, Meng Wang, Sen Wang
Scalable Estimator for Multi-task Gaussian Graphical Models Based in an IoT Network. ACM Trans. Sens. Networks 17 (3) (2021)
Arshdeep Sekhon, Beilun Wang, Zhe Wang, Yanjun Qi
Differential Network Learning Beyond Data Samples. CoRR (2020)
Jiayi Yuan, Hongye Li, Meng Wang, Ruyang Liu, Chuanyou Li, Beilun Wang
An OpenCV-based Framework for Table Information Extraction. ICKG (2020)
Jiaqi Zhang, Meng Wang, Qinchi Li, Sen Wang, Xiaojun Chang, Beilun Wang
Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables. IJCAI (2020)
Beilun Wang, Rui Ma, Jingyu Kuang, Yan Zhang
How Decisions Are Made in Brains: Unpack "Black Box" of CNN With Ms. Pac-Man Video Game. IEEE Access 8 (2020)
Jiaqi Zhang, Beilun Wang
Fast and Scalable Estimator for Sparse and Unit-Rank Higher-Order Regression Models. CoRR (2019)
Jiaqi Zhang, Beilun Wang
Sparse and Low-Rank Tensor Regression via Parallel Proximal Method. CoRR (2019)
Beilun Wang, Arshdeep Sekhon, Yanjun Qi
Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. AISTATS (2018)
Beilun Wang, Arshdeep Sekhon, Yanjun Qi
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models. CoRR (2018)
Beilun Wang, Arshdeep Sekhon, Yanjun Qi
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models. ICML (2018)
Ritambhara Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, Yanjun Qi
GaKCo: A Fast Gapped k-mer String Kernel Using Counting. ECML/PKDD (1) (2017)
Beilun Wang, Ji Gao, Yanjun Qi
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. AISTATS (2017)
Jack Lanchantin, Ritambhara Singh, Beilun Wang, Yanjun Qi
Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. PSB (2017)
Beilun Wang, Arshdeep Sekhon, Yanjun Qi
Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. CoRR (2017)
Ji Gao, Beilun Wang, Zeming Lin, Weilin Xu, Yanjun Qi
DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples. ICLR (Workshop) (2017)
Ji Gao, Beilun Wang, Yanjun Qi
DeepMask: Masking DNN Models for robustness against adversarial samples. CoRR (2017)
Beilun Wang, Ji Gao, Yanjun Qi
A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Samples. ICLR (Workshop) (2017)
Chandan Singh, Beilun Wang, Yanjun Qi
A Constrained, Weighted-L1 Minimization Approach for Joint Discovery of Heterogeneous Neural Connectivity Graphs. CoRR (2017)
Beilun Wang, Ritambhara Singh, Yanjun Qi
A constrained $$\ell $$ ℓ 1 minimization approach for estimating multiple sparse Gaussian or nonparanormal graphical models. Mach. Learn. 106 (9-10) (2017)
Beilun Wang, Ji Gao, Yanjun Qi
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. CoRR (2017)
Ritambhara Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, Yanjun Qi
GaKCo: a Fast GApped k-mer string Kernel using COunting. CoRR (2017)
Beilun Wang, Ritambhara Singh, Yanjun Qi
A constrained L1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models. CoRR (2016)
Jack Lanchantin, Ritambhara Singh, Beilun Wang, Yanjun Qi
Deep GDashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. CoRR (2016)
Feiyu Xiong, Moshe Kam, Leonid Hrebien, Beilun Wang, Yanjun Qi
Kernelized Information-Theoretic Metric Learning for Cancer Diagnosis Using High-Dimensional Molecular Profiling Data. ACM Trans. Knowl. Discov. Data 10 (4) (2016)
Beilun Wang, Ji Gao, Yanjun Qi
A Theoretical Framework for Robustness of (Deep) Classifiers Under Adversarial Noise. CoRR (2016)