17 citations · 23 across the 9 of their papers we have counts for
9 papers
Direct sampling methods for inverse medium scattering problems of elastic waves
Lu Zhao, Yiling Li, Zhiyong Cheng
This paper concerns the inverse elastic scattering problem of determining an unknown penetrable obstacle from far-field data. Using the Helmholtz decomposition, the coupled boundar…
A novel time-domain iterative method for a three-dimensional inverse acoustic obstacle scattering problem
Lu Zhao, Heping Dong, Zhiyong Cheng
This paper concerns the three-dimensional forward and inverse acoustic obstacle scattering problem in the time domain. For the forward problem, a retarded potential formulation dis…
A highly efficient iterative approach for inverse acoustic obstacle scattering problems in three dimensions
Zhiyong Cheng, Heping Dong, Lu Zhao
This paper concerns a three-dimensional inverse acoustic obstacle scattering problem from scattered field or phased/phaseless far-field data. Based on the boundary integral defined…
Behavior-Contextualized Item Preference Modeling for Multi-Behavior Recommendation
Mingshi Yan, Fan Liu, Jing Sun +3
In recommender systems, multi-behavior methods have demonstrated their effectiveness in mitigating issues like data sparsity, a common challenge in traditional single-behavior reco…
Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation
Zhiyong Cheng, Jianhua Dong, Fan Liu +3
Multi-behavioral recommender systems have emerged as a solution to address data sparsity and cold-start issues by incorporating auxiliary behaviors alongside target behaviors. Howe…
Cluster-based Graph Collaborative Filtering
Fan Liu, Shuai Zhao, Zhiyong Cheng +2
Graph Convolution Networks (GCNs) have significantly succeeded in learning user and item representations for recommendation systems. The core of their efficacy is the ability to ex…