Some interesting conferences you may explore for papers to present:

• ACL/HLT (Association of Computational Linguistics/Human Language Technologies
• AMIA (American Medical Informatics Association) and JAMIA
• ACM SIGIR (Special Interest Group in Information Retrieval)
• AIRS - Asian Information Retrieval
• ICML (International Conference on Machine Learning)
• ICWSM (AAAI Conference on Web and Social Media)
• ACM KDD (Knowledge Discovery and Data Mining)
• WWW (World Wide Web Conference)
• WSDM (ACM International Conference on Web Search and Data Mining)
• TREC Proceedings
• arXiV

Goal: To study current papers from journals and conference proceedings in text retrieval and text mining. Examples of problems include topic models, web retrieval and web mining, ranking strategies, ambiguity resolution, knowledge discovery, web phenomenon including social networks, information extraction and text classification. The reading group is lead by Professor Padmini Srinivasan. Interested students (from beginning to advanced students) and faculty are invited to participate in the reading group. Participation format is informal with individuals taking turns to present an overview of the selected paper and lead the discussion. This forum has resulted in collaborative projects and published papers.

1. January 28: Momina Tabish, UCC-2520C-Conf
• Ma, F., Gao, J., Suo, Q., You, Q., Zhou, J., & Zhang, A. (2018, July). Risk prediction on electronic health records with prior medical knowledge. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 1910-1919). ACM.
2. February 4: Asad Mahmood - UCC-2520C-Conf
• Feng, J., Huang, M., Zhao, L., Yang, Y., & Zhu, X. (2018, April). Reinforcement learning for relation classification from noisy data. In Thirty-Second AAAI Conference on Artificial Intelligence.
3. February 11: Jonathan Russert - UCC-2520B-Conf
• Founta, A. M., Chatzakou, D., Kourtellis, N., Blackburn, J., Vakali, A., & Leontiadis, I. (2019, June). A unified deep learning architecture for abuse detection. In Proceedings of the 10th ACM Conference on Web Science (pp. 105-114). ACM.
4. February 18: Huyen Le - UCC-2520B-Conf
• Zannettou, S., Caulfield, T., Blackburn, J., De Cristofaro, E., Sirivianos, M., Stringhini, G., & Suarez-Tangil, G. (2018, October). On the origins of memes by means of fringe web communities. In Proceedings of the Internet Measurement Conference 2018 (pp. 188-202). ACM.
5. February 25: Dat Hong - UCC-2390-Exec
• Lei, T., Barzilay, R., & Jaakkola, T. (2016). Rationalizing neural predictions. arXiv preprint arXiv:1606.04155.
6. March 4: Osama Khalid - UCC-2520B-Conf
• Hazarika, D., Poria, S., Gorantla, S., Cambria, E., Zimmermann, R., & Mihalcea, R. (2018). CASCADE: Contextual sarcasm detection in online discussion forums. arXiv preprint arXiv:1805.06413.
7. March 11: Ingroj Shrestha - UCC-2520B-Conf
• Hwang, U., Choi, S., Lee, H. B., & Yoon, S. (2017). Adversarial Training for Disease Prediction from Electronic Health Records with Missing Data. arXiv preprint arXiv:1711.04126.
8. March 18: Spring Break
9. March 25: Cancelled
10. April 1: Asad Mahmood - UCC-2520B-Conf
• Lample, G., Subramanian, S., Smith, E., Denoyer, L., & Boureau, Y. L. (2018). Multiple-attribute text rewriting.
11. April 8: Momina Tabish - UCC-2520B-Conf
• Che, Z., Sauver, J. S., Liu, H., & Liu, Y. (2017). Deep learning solutions for classifying patients on opioid use. In AMIA Annual Symposium Proceedings (Vol. 2017, p. 525). American Medical Informatics Association.
12. April 15: Cancelled
13. April 22: Ingroj Shrestha - UCC-2520B-Conf
• Zhang, J., Kowsari, K., Harrison, J. H., Lobo, J. M., & Barnes, L. E. (2018). Patient2vec: A personalized interpretable deep representation of the longitudinal electronic health record. IEEE Access, 6, 65333-65346.
14. April 29: Jonathan Rusert - UCC-2520C-Conf
• Damiani, M. L., Silvestri, C., & Bertino, E. (2011). Fine-grained cloaking of sensitive positions in location-sharing applications. IEEE Pervasive Computing, 10(4), 64-72.
15. May 6: Dat Hong - UCC-2520B-Conf
• Ehsan, U., Harrison, B., Chan, L., & Riedl, M. O. (2018, December). Rationalization: A neural machine translation approach to generating natural language explanations. In Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society (pp. 81-87). ACM.