- 📖 Dissertation: Multi-view fuzzy clustering algorithms for multi-view data (In Chinese: 多視圖數據模糊聚類演算法); Advised by Prof. Miin-Shen Yang.
- 🎮 I am a lifelong learner and driven by community.
- 💡 I have worked on various unsupervised learning techniques, including clustering, dimensionality reduction, and anomaly detection. In my most recent project, I developed a new approach to clustering that leverages deep learning models to achieve improved accuracy and scalability.
Strong Languages: Matlab, R and Python/TensorFlow
| Name | Completed | URL | Organizations |
|---|---|---|---|
| Machine Learning Specialization | OCT 26, 2022 |
Certificate | Coursera |
| DeepLearning.AI TensorFlow Developer Specialization | NOV 16, 2022 |
Certificate | Coursera |
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Yang, M. S., Sinaga, K. P. (2021). Collaborative feature-weighted multi-view fuzzy c-means clustering. Pattern Recognition, 119, 108064.
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Sinaga, K. P., Hussain, I., Yang, M. S. (2021). Entropy K-means clustering with feature reduction under unknown number of clusters. IEEE Access, 9, pp: 67736-67751.
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Sinaga, K. P., Yang, M. S. (2020). Unsupervised K-means clustering algorithm. IEEE Access, 8, pp: 80716-80727.
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Yang, M. S., Sinaga, K. P. (2019). A feature-reduction multi-view k-means clustering algorithm. IEEE Access, 7, pp: 114472-114486.
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Sinaga, K. P., Hsieh, J. N., Benjamin, J., Yang, M. S. (2018). Modified relational mountain clustering method. In International Conference on Artificial Intelligence and Soft Computing, pp: 690-701.
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[On Progress] Hussain, I., Sinaga, K. P., Yang, M. S. Unsupervised multi-view fuzzy c-means.
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[On Progress] Sinaga, K. P. Multi-view learning disagreement-based entropy-gaussian-kernel.
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[Ongoing Research] Sinaga, K. P. A comprehensive validity index for multi-view machine learning.
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[Ongoing Research] Sinaga, K. P. Regularized multi-label view reduction without supervision.
If you are interested in more details, check out my website or my CV
📫: kristinasinaga57@yahoo.co.id (Primary)