Graphzoom: A multi-level spectral approach for accurate and scalable graph embedding C Deng, Z Zhao, Y Wang, Z Zhang, Z Feng arXiv preprint arXiv:1910.02370, 2019 | 141 | 2019 |
Spectrum-preserving sparsification for visualization of big graphs M Imre, J Tao, Y Wang, Z Zhao, Z Feng, C Wang Computers & Graphics 87, 89-102, 2020 | 26 | 2020 |
SAMG: Sparsified graph-theoretic algebraic multigrid for solving large symmetric diagonally dominant (SDD) matrices Z Zhao, Y Wang, Z Feng 2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 601-606, 2017 | 20 | 2017 |
A spectral graph sparsification approach to scalable vectorless power grid integrity verification Z Zhao, Z Feng Proceedings of the 54th Annual Design Automation Conference 2017, 1-6, 2017 | 15 | 2017 |
Spade: A spectral method for black-box adversarial robustness evaluation W Cheng, C Deng, Z Zhao, Y Cai, Z Zhang, Z Feng International Conference on Machine Learning, 1814-1824, 2021 | 14 | 2021 |
Towards scalable spectral embedding and data visualization via spectral coarsening Z Zhao, Y Zhang, Z Feng Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 14 | 2021 |
Scalable graph topology learning via spectral densification Y Wang, Z Zhao, Z Feng Proceedings of the Fifteenth ACM international Conference on Web search and …, 2022 | 13 | 2022 |
SF-GRASS: solver-free graph spectral sparsification Y Zhang, Z Zhao, Z Feng Proceedings of the 39th International Conference on Computer-Aided Design, 1-8, 2020 | 13 | 2020 |
Effective-resistance preserving spectral reduction of graphs Z Zhao, Z Feng Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 13 | 2019 |
Nearly-linear time spectral graph reduction for scalable graph partitioning and data visualization Z Zhao, Y Wang, Z Feng arXiv preprint arXiv:1812.08942, 2018 | 12 | 2018 |
Hypersf: Spectral hypergraph coarsening via flow-based local clustering A Aghdaei, Z Zhao, Z Feng 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-9, 2021 | 6 | 2021 |
Graspel: Graph spectral learning at scale Y Wang, Z Zhao, Z Feng arXiv preprint arXiv:1911.10373, 2019 | 5 | 2019 |
A unified approach to scalable spectral sparsification of directed graphs Y Zhang, Z Zhao, Z Feng arXiv preprint arXiv:1812.04165, 2018 | 5 | 2018 |
Sf-sgl: Solver-free spectral graph learning from linear measurements Y Zhang, Z Zhao, Z Feng IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2022 | 3 | 2022 |
Towards scalable spectral sparsification of directed graphs Y Zhang, Z Zhao, Z Feng 2019 IEEE International Conference on Embedded Software and Systems (ICESS), 1-2, 2019 | 3 | 2019 |
A spectral approach to scalable vectorless thermal integrity verification Z Zhao, Z Feng 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), 412-417, 2020 | 2 | 2020 |
diGRASS: Directed Graph Spectral Sparsification via Spectrum-Preserving Symmetrization Y Zhang, Z Zhao, Z Feng ACM Transactions on Knowledge Discovery from Data 18 (4), 1-25, 2024 | 1 | 2024 |
A Multilevel Spectral Framework for Scalable Vectorless Power/Thermal Integrity Verification Z Zhao, Z Feng ACM Transactions on Design Automation of Electronic Systems 28 (1), 1-25, 2022 | | 2022 |
High-Performance Spectral Methods for Computer-Aided Design of Integrated Circuits Z Zhao Michigan Technological University, 2020 | | 2020 |
Graph Learning via Spectral Densification Z Feng, Y Wang, Z Zhao | | |