Publications

Journal

[J1] Kim, Y.-G., Lee, K., and Paik, M.C. (2022). Conditional Wasserstein generator. IEEE Transactions on Pattern Analysis and Machine Intelligence. [Paper] [Code]

[J2] Lee, J.-S., Han, D., Kim, S.Y., Hong, K.H., Jang, M.-j., Kim, M.J., Kim, Y.-g., Park, J.H., Cho, S.I., Park, W.B., Lee, K., Shin, H.S., Oh, H.S., Kim, T.S., Park, S.S., and Seong, M.-W. (2021). Longitudinal proteomic profiling provides insights into host response and proteome dynamics in COVID‐19 progression. Proteomics. [Paper]

[J3] Lee, J.-S., Lee, K., Song, H., Sun, C., Kim, M.J., Cho, S.I., Lee, Y.K., Park, S.S., and Seong, M.-W. (2021). Noninvasive prenatal test of single-gene disorders by linked-read direct haplotyping: application in various diseases. European Journal of Human Genetics. [Paper]

[J4] Lee, J.-S., Lee, K., Song, H., Sun, C., Kim, M.J., Cho, S.I., Lee, Y.K., Park, S.S., and Seong, M.-W. (2020). Direct haplotyping-based noninvasive prenatal test for myotonic dystrophy type 1 with large CTG expansion. Clinical Chemistry. [Paper]

Peer-reviewed Conference

[C1] Lee, K., Paik, M.C., Oh, M.-h., and Kim, G.-S. (2024). Mixed-Effects Contextual Bandits. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2024). [Paper] [Code]

[C2] Kim, W., Lee, K., and Paik, M.C. (2023). Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2023). [Paper]

Patent

[Patent 1] Paik, M.C., Kim, Y.-G., and Lee, K. Method and apparatus for conditional data generation using conditional Wasserstein generator. Republic of Korea Patent. [Info]

Preprint

[Pre. 1] Lee, K., and Paik, M.C. (2024). Doubly-Robust Off-Policy Evaluation with Estimated Logging Policy. [ArXiv]

[Pre. 2] Kim, Y.-G., Lee, K., Choi., Y., Won., J.-H., and Paik, M.C. (2023). Wasserstein geodesic generator for conditional distributions (under Major Revision at Journal of Machine Learning Research). [ArXiv] [Code]