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Posts by Collection
portfolio
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publications
Laplacian-based Cluster-Contractive t-SNE for High-Dimensional Data Visualization
Published in ACM Transactions on Knowledge Discovery from Data, 2023
Dimension Reduction: Enhances t-SNE by leveraging graph Laplacian for better cluster preservation, outperforming t-SNE and UMAP in structure and visualization.
Citation: Sun, Y., Han, Y., & Fan, J. (2023). Laplacian-based Cluster-Contractive t-SNE for High-Dimensional Data Visualization. ACM Transactions on Knowledge Discovery from Data, 18(1), 1-22.
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Deep orthogonal hypersphere compression for anomaly detection
Published in The Twelfth International Conference on Learning Representations (Spotlight), 2024
Anomaly Detection: Introduces hypersphere-based methods (DOHSC, DO2HSC) for anomaly detection, including graph-level cases, offering compact decision regions and improved accuracy.
Citation: Zhang, Y., Sun, Y., Cai, J., & Fan, J. (2024). Deep orthogonal hypersphere compression for anomaly detection. In The Twelfth International Conference on Learning Representations.
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MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy
Published in The Twelfth International Conference on Learning Representations (Spotlight), 2024
Graph Metric Learning: Proposes MMD-GK, a graph kernel method with unsupervised and supervised variants, achieving superior results in graph clustering and classification tasks.
Citation: Sun, Y., & Fan, J. (2024). MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy. In The Twelfth International Conference on Learning Representations.
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Unsupervised Multiple Kernel Learning for Graphs via Ordinality Preservation
Published in The Thirteen International Conference on Learning Representations, 2025
Graph Metric Learning: Proposes UMKL-G, which combines multiple graph kernels in an unsupervised way, preserving the ordinal relationships between graphs.
Citation: Sun, Y., & Kok, S. (2025). Unsupervised Multiple Kernel Learning for Graphs via Ordinality Preservation. In The Thirteen International Conference on Learning Representations.
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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