Difference between revisions of "CSE 7300 Research Seminar"

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Revision as of 19:18, 27 March 2024

  • Theme: AI for Health
  • Instructor: Prof. Chenyang Lu
  • Semester: Spring 2024
  • Time: Wednesday at 1 PM
  • Location: McKelvey 1030
  • Guidelines:
  • Recommended sources: NeurIPS ([1]), ICML ([2]), AAAI ([3]), SIGKDD ([4]), IJCAI ([5]), IMWUT ([6]), HEALTH ([7]), Digital Medicine ([8]), Lancet Digital Health ([9]), NEJM AI ([10])

Presentation Schedule

---Jan 24 ---

Hangyue

Krishnamachari, Kiran, See-Kiong Ng, and Chuan-Sheng Foo. "Mitigating Real-World Distribution Shifts in the Fourier Domain." Transactions on Machine Learning Research (2023). [11]

---Jan 31 ---

Ruiqi

Faure, Gueter Josmy, Min-Hung Chen, and Shang-Hong Lai. "Holistic interaction transformer network for action detection." In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 3340-3350. 2023. [12]

---Feb 07 ---

Jizhou

Parikh, Harsh, Quinn Lanners, Zade Akras, Sahar F. Zafar, M. Brandon Westover, Cynthia Rudin, and Alexander Volfovsky. "Estimating Trustworthy and Safe Optimal Treatment Regimes." arXiv preprint arXiv:2310.15333 (2023). [13]

---Feb 14 ---

Ben

M. Wornow, R. Thapa, E. Steinberg, J. A. Fries, and N. H. Shah, “EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models.” arXiv, Dec. 11, 2023. doi: 10.48550/arXiv.2307.02028.

L. L. Guo et al., “A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records.” arXiv, Nov. 19, 2023. Available: http://arxiv.org/abs/2311.11483

---Feb 21 ---

Quan

Maus, N., Jones, H., Moore, J., Kusner, M. J., Bradshaw, J., & Gardner, J. (2022). Local latent space bayesian optimization over structured inputs. Advances in Neural Information Processing Systems, 35, 34505-34518. [14]

---Feb 28 ---

Ziqi

Oral exam practice

[1] Udandarao, Vishaal, et al. “COBRA: Contrastive Bi-Modal Representation Algorithm”, IJCAI (TUSION workshop) 2020. [15]

[2] Han Zongbo, et al. “Trusted Multi-View Classification.” International Conference on Learning Representations (ICLR). 2020. [16]

[3] Zhenbang Wu et al. “Multimodal Patient Representation Learning with Missing Modalities and Labels”. International Conference on Learning Representations(ICLR), 2024. [17]

---Mar 06 ---

Jiaming

Zhang, Nan, Yusen Zhang, Wu Guo, Prasenjit Mitra, and Rui Zhang. "FaMeSumm: Investigating and Improving Faithfulness of Medical Summarization." In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp. 10915-10931. 2023. [18]

---Mar 13 ---

Spring Break

---Mar 20 ---

Charles

Van Veen, Dave, Cara Van Uden, Louis Blankemeier, Jean-Benoit Delbrouck, Asad Aali, Christian Bluethgen, Anuj Pareek et al. "Adapted large language models can outperform medical experts in clinical text summarization." Nature Medicine (2024): 1-9. [19]

Liu, Nelson F., Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. "Lost in the Middle: How Language Models Use Long Contexts." Transactions of the Association for Computational Linguistics 12 (2024). [20]

---Mar 27 ---

Jingwen

Gouareb, Racha, Alban Bornet, Dimitrios Proios, Sónia Gonçalves Pereira, and Douglas Teodoro. "Detection of Patients at Risk of Multidrug-Resistant Enterobacteriaceae Infection Using Graph Neural Networks: A Retrospective Study." Health Data Science 3 (2023): 0099. [21]

---Apr 03 ---

Hanyang

---Apr 10 ---

Zebo

---Apr 17 ---

Claire

---Apr 24 ---

Daoyi


Previous Semesters

Previous Lab Meetings

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