Difference between revisions of "CSE 7300 Research Seminar"
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Rumi, Masuma Akter, et al. "Accelerating sparse cnn inference on gpus with performance-aware weight pruning." Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques. 2020. [https://dl.acm.org/doi/abs/10.1145/3410463.3414648] | Rumi, Masuma Akter, et al. "Accelerating sparse cnn inference on gpus with performance-aware weight pruning." Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques. 2020. [https://dl.acm.org/doi/abs/10.1145/3410463.3414648] | ||
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=== ---Apr 12 ---=== | === ---Apr 12 ---=== | ||
Charles | Charles | ||
| − | Hao, B., Zhu, H., & Paschalidis, I. C. (2020, December). Enhancing clinical bert embedding using a biomedical knowledge base. In 28th International Conference on Computational Linguistics | + | Hao, B., Zhu, H., & Paschalidis, I. C. (2020, December). Enhancing clinical bert embedding using a biomedical knowledge base. In 28th International Conference on Computational Linguistics [https://aclanthology.org/2020.coling-main.57/] |
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| + | Logé, C., Ross, E., Dadey, D. Y. A., Jain, S., Saporta, A., Ng, A. Y., & Rajpurkar, P. (2021). Q-Pain: a question answering dataset to measure social bias in pain management. Neural Information Processing Systems 2021 [https://doi.org/10.13026/2tdv-hj07] | ||
=== ---Apr 19 ---=== | === ---Apr 19 ---=== | ||
Revision as of 04:46, 13 April 2023
- Theme: AI and IoT for Medicine (AIM)
- Instructor: Prof. Chenyang Lu
- Semester: Spring 2023
- Time: Wednesday at 11am-12pm
- 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]), SenSys, MobiSys, MobiCom
Presentation Schedule
---Jan 25 ---
Jaehwan
Jeong, Joo Seong, et al. "Band: coordinated multi-DNN inference on heterogeneous mobile processors." Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services. 2022.[10]
---Feb 01 ---
Hanyang
Contrastive multiview learning and its applications
Tian, Yonglong, Dilip Krishnan, and Phillip Isola. "Contrastive multiview coding." Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XI 16. Springer International Publishing, 2020. [11]
Other related papers:
InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training
Contrastive Learning with Cross-Modal Knowledge Mining for Multimodal Human Activity Recognition
Multi-level Feature Learning for Contrastive Multi-view Clustering
---Feb 08 ---
Ziqi
Mingcheng Chen. et al. Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD ’21). Association for Computing Machinery, New York, NY, USA, 2663–2673.[12]
---Feb 15 ---
Ruiqi
Chao-Yuan Wu, Yanghao Li, Karttikeya Mangalam, Haoqi Fan, Bo Xiong, Jitendra Malik, Christoph Feichtenhofer; MeMViT: Memory-Augmented Multiscale Vision Transformer for Efficient Long-Term Video Recognition. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, pp. 13587-13597 [13]
---Feb 22 ---
Melanie
F. Cheng et al., "VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models," in IEEE Transactions on Visualization and Computer Graphics, vol. 28, no. 1, pp. 378-388, Jan. 2022, doi: 10.1109/TVCG.2021.3114836. [14]
---Mar 01 ---
Jingwen
Malinin, Andrey, Liudmila Prokhorenkova, and Aleksei Ustimenko. “Uncertainty in Gradient Boosting via Ensembles.” International Conference on Learning Representations, 2021. [15]
---Mar 08 ---
Andrew
Martinez, Natalia, Martin Bertran, and Guillermo Sapiro. "Minimax pareto fairness: A multi objective perspective." International Conference on Machine Learning. PMLR, 2020. [16].
---Mar 15 ---
Spring Break
---Mar 22 ---
Bye Week
---Mar 29 ---
Hangyue
---Apr 05 ---
Ye
Rumi, Masuma Akter, et al. "Accelerating sparse cnn inference on gpus with performance-aware weight pruning." Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques. 2020. [17]
---Apr 12 ---
Charles
Hao, B., Zhu, H., & Paschalidis, I. C. (2020, December). Enhancing clinical bert embedding using a biomedical knowledge base. In 28th International Conference on Computational Linguistics [18]
Logé, C., Ross, E., Dadey, D. Y. A., Jain, S., Saporta, A., Ng, A. Y., & Rajpurkar, P. (2021). Q-Pain: a question answering dataset to measure social bias in pain management. Neural Information Processing Systems 2021 [19]
---Apr 19 ---
Bing
Poulain, Raphael, Mehak Gupta, and Rahmatollah Beheshti. "Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records." (2022). [20]
---Apr 26 ---
Previous Semesters
- Fall 2022
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