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Toan_master_thesis(19th_Aug)
Acknowledgments
What is Network Alignment?
Heterogeneous Network Representation by Network Alignment
Pattern recognition and image processing
Research Outcomes
The pilot study I: Weakly-supervised network alignment
The pilot study II: Unsupervised network alignment
RESEARCH BACKGROUND AND PROBLEM STATEMENT
Background
Network
WEAKLY-SUPERVISED NETWORK ALIGNMENT: A Pilot Study
Main contributions
Network alignment
Rough alignment under a GAN-based setting
Evaluations
Comparative performance to unsupervised methods
Comparative performance to supervised methods
UNSUPERVISED NETWORK ALIGNMENT: A Pilot Study
Main contributions
Reconciling embedding spaces
Rough alignment under a GAN-based setting
Alignment Performance Analysis
Robustness to structural noise
Robustness to graph size imbalance
CONCLUSION
Summary of the work
Novelty of the thesis outcomes
Limitations and Future Directions
Appendix A: General Experimental Settings
Datasets
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