Partial Multi-Label Learning: A Comprehensive Survey of Learning Strategies, Extensions, Evaluation Practices, and Future Directions
Manuscript · Under review
Ph.D. Candidate Machine Learning
Dongyeon Kim
Multi-label learning, weakly supervised learning, and distance metric learning.
Research on machine learning algorithms for data with multiple labels, incomplete supervision, or ambiguous annotations, with an additional interest in data-driven solutions to real-world problems.
Research
Learning from multi-label & weakly supervised data
Multi-label learning
Developing learning algorithms for classifying data instances associated with multiple labels.
Weakly supervised learning
Design classification algorithms for real-world data with incomplete or ambiguous supervision.
Distance metric learning
Design distance metric learning methods to capture task-relevant similarities and support classification and clustering.
Education
Ph.D. in Computer Science and Artificial Intelligence
Dongguk University, Seoul, South Korea · Advisor: Prof. Gangman Yi
Expected graduation: Aug. 2027
M.S. in Multimedia Engineering
Dongguk University, Seoul, South Korea · Advisor: Prof. Gangman Yi
Thesis: A Study on Parameter Automation Algorithm for Clustering-based Multi-metric Learning
B.S. in Multimedia Engineering
Dongguk University, Seoul, South Korea
Graduated with Highest Honors
Publications
Manuscripts, journal articles, and conference papers.
Manuscripts
5 manuscriptsResearch in progress; not yet published.
From Crime Analysis to Operational Policing: Real-World Validation of Hotspot-Based Patrol Route Optimisation
Manuscript · Under review
Pseudo-label Correlation-aware Contrastive Learning for Multi-Labeled Complementary Label Learning
Manuscript · In revision
Crime-Risk-Based Patrol Route Optimization for Crime Prevention in Urban Road Networks
Manuscript · In revision
Label-Specific Disambiguation via Distance Metric Learning for Partial Multi-Label Classification
Manuscript · In revision
Journal articles
7 papersA Method for Consensus Anchor Graph Learning for Incomplete Multi-View Clustering
IEEE Access, 14, 18155–18168 (2026)
GapSense: Similarity estimation-based gap filler with TGS-reads for genome assemblies
Interdisciplinary Sciences: Computational Life Sciences, 18(2), 501–514 (2026)
DeepPI: Alignment-free analysis of flexible length proteins based on deep learning and image generator
Interdisciplinary Sciences: Computational Life Sciences, 16(3), 1–12 (2024)
AutoSCAN: Automatic detection of DBSCAN parameters and efficient clustering of data in overlapping density regions
PeerJ Computer Science, 10, e1921 (2024)
Parameter-Free Basis Allocation for Efficient Multiple Metric Learning
Machine Learning: Science and Technology, 4(4), 045049 (2023)
Hotspots-based patrol route optimization algorithm for smart policing
Heliyon, 9(10), e20931 (2023)
cPlot: Contig-Plotting Visualization for the Analysis of Short-Read Nucleotide Sequence Alignments
International Journal of Molecular Sciences, 23(19), 11484 (2022)
Conference papers
3 papersT-MDML: Triplet-based multiple distance metric learning for multi-instance multi-label classification with label correlation
Proceedings of the AAAI Conference on Artificial Intelligence, 39(17), 17850–17858 (2025)
A Novel Gap-Filling Method Based on Hybrid Read Information Analysis
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 3827–3829 (2022)
Novel Patrol Route Optimization Method Based on Big Data Analysis
IEEE International Conference on Big Data, 6699–6701 (2022)
Conference papers (Korea)
3 papersHS Code Classification Using Graph RAG with an HS Explanatory Notes-Based Knowledge Graph
Proceedings of the Korea Computer Congress (KCC), 324–326 (2026) · In Korean
Public Data-Based Hotspot Detection and Patrol Route Optimization with Spatiotemporal Data
Proceedings of the Korea Computer Congress (KCC), 414–416 (2024) · In Korean
BLAST-Based Gap Analysis for Gap Filling Algorithm
Proceedings of the Korea Computer Congress (KCC), 1625–1627 (2022) · In Korean
Conference presentations and contributions, teaching experience, and other academic activities are listed in the CV (PDF) ↗.
Selected highlights
Additional details are available in the CV.
Oct. 2025
Outstanding Next-Generation Engineering Researcher Award · IPESK, South Korea
2023
– 2025
– 2025
Dongguk Global Fellowship · Dongguk University · Four semesters
2021–2022,
2024–2026
2024–2026
Teaching Assistant · Undergraduate computer science courses at Dongguk University
Contact
For research inquiries or collaborations, feel free to get in touch.