Multimodal Recommendation (2024, December) [slides]
Cold-start Item Recommendation (2024, August) [slides]
Link Prediction (2024, June) [slides]
Music Embeddings (2024, April) [slides]
A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios [paper] | [slides]
Ganhör, C., Moscati, M., Hausberger, A., Nawaz, S., & Schedl, M. (2024, October). ACM Conference on Recommender Systems.
Cold-Start Next-Item Recommendation by User-Item Matching and Auto-Encoders [paper] | [slides]
Wu, H., Wong, C. W., Zhang, J., Yan, Y. et al. (2023). IEEE Transactions on Services Computing.
Attribute Graph Neural Networks for Strict Cold-Start Recommendation [paper] | [slides]
Qian, T., Liang, Y., Li, Q., & Xiong, H. (2020). IEEE Transactions on Knowledge and Data Engineering.
Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation [paper] | [slides]
Chen, Y., Yang, Y., Wang, Y., Bai, J., Song, X., & King, I. (2022, May). IEEE International Conference on Data Engineering.
Music Recommendation via Hypergraph Embedding [paper] | [slides]
La Gatta, V., Moscato, V., Pennone, M. et al. (2022). IEEE transactions on neural networks and learning systems.
Contextual and Sequential User Embeddings for Large-Scale Music Recommendation [paper] | [slides]
Hansen, C., Hansen, C., Maystre, L. et al. (2020, September). ACM Conference on Recommender Systems.
MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training [paper] | [slides]
Li, Y. et al. (2023). arXiv preprint.
MuLan: A Joint Embedding of Music Audio and Natural Language [paper] | [slides]
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SSAST: Self-Supervised Audio Spectrogram Transformer [paper] | [slides]
Gong, Y., Lai, C. I., Chung, Y. A., & Glass, J. (2022). AAAI Conference on Artificial Intelligence.
A Deep Learning-based Precision and Automatic Kidney Segmentation System Using Efficient Feature Pyramid Networks in Computed Tomography Images [paper] | [slides]
Hsiao, C. H. et al. (2022). Computer Methods and Programs in Biomedicine.
FaceNet: A unified embedding for face recognition and clustering [paper] | [slides]
Schroff, F., Kalenichenko, D., & Philbin, J. (2015). IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
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Keshav, S. (2007). ACM SIGCOMM Computer Communication Review.