DAIS Qual Exam Time & Reading List (Spring 2022)

The DAIS Qual Exam in Spring 2022 has been scheduled to be at 1-5pm on Monday, Feb. 28, 2022. 

This reading list consists of  multiple topic sections, each containing 2-3 papers.  The questions in the written exam will be based on the papers listed here, with 1-2 questions related to each section. That is, if a section has two papers, you can expect to see one question related to the section in the qual exam, while if a section has three papers, you can expect to see two questions related to the section.

Section 1

  • Maria Maistro, Lucas Chaves Lima, Jakob Grue Simonsen, and Christina Lioma. 2021. Principled Multi-Aspect Evaluation Measures of Rankings. Proceedings of the 30th ACM International Conference on Information & Knowledge Management. Association for Computing Machinery, New York, NY, USA, 1232–1242. DOI:https://doi.org/10.1145/3459637.3482287 PDF file: http://www.library.illinois.edu/proxy/go.php?url=https://dl.acm.org/doi/pdf/10.1145/3459637.3482287
  • Naseri S., Dalton J., Yates A., Allan J. (2021) CEQE: Contextualized Embeddings for Query Expansion. In: Hiemstra D., Moens MF., Mothe J., Perego R., Potthast M., Sebastiani F. (eds) Advances in Information Retrieval. ECIR 2021. Lecture Notes in Computer Science, vol 12656. Springer, Cham. https://doi.org/10.1007/978-3-030-72113-8_31  PDF file:  https://link.springer.com/content/pdf/10.1007%2F978-3-030-72113-8_31.pdf
  • Salle A., Malmasi S., Rokhlenko O., Agichtein E. (2021) Studying the Effectiveness of Conversational Search Refinement Through User Simulation. In: Hiemstra D., Moens MF., Mothe J., Perego R., Potthast M., Sebastiani F. (eds) Advances in Information Retrieval. ECIR 2021. Lecture Notes in Computer Science, vol 12656. Springer, Cham. https://doi.org/10.1007/978-3-030-72113-8_39. PDF file: https://link.springer.com/content/pdf/10.1007%2F978-3-030-72113-8_39.pdf

Section 2

Section 3

  • Jan Overgoor, Austin Benson, and Johan Ugander. Choosing to grow a graph: modeling network formation as discrete choice. In The World Wide Web Conference, pages 1409–1420. ACM, 2019. https://arxiv.org/abs/1811.05008
  • Yuxin Xiao, Adit Krishnan, and Hari Sundaram. Discovering strategic behaviors for collaborative content-production in social networks. In The Web Conference (WebConf 2020), pages 2078–2088, Taipei, Taiwan, April 2020.  https://arxiv.org/abs/2003.03670
  • Harshay Shah, Suhansanu Kumar, and Hari Sundaram. Growing attributed networks through local processes. In The World Wide Web Conference – WWW ’19, pages 3208–3214. ACM Press, May 2019.   https://arxiv.org/abs/1712.10195


  • Hongwei Wang, Weijiang Li, Xiaomeng Jin, Kyunghyun Cho, Heng Ji, Jiawei Han and Martin Burke. 2022. Chemical-Reaction-aware Molecule Representation Learning. Proc. The International Conference on Learning Representations (ICLR2022). https://blender.cs.illinois.edu/paper/moleculerepresentation2021a.pdf
  • Yiwei Luo, Dallas Card and Dan Jurafsky. 2020. Detecting Stance in Media on Global Warming. Proc. The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020). https://aclanthology.org/2020.findings-emnlp.296v3.pdf
  • Yi R. Fung, Christopher Thomas, Revanth Gangi Reddy, Sandeep Polisetty, Heng Ji, Shih-Fu Chang, Kathleen McKeown, Mohit Bansal and Avi Sil. 2021. InfoSurgeon: Cross-Media Fine-grained Information Consistency Checking for Fake News Detection. Proc. The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021). https://blender.cs.illinois.edu/paper/infosurgeon2021.pdf

Section 5

Section 6

  • Fu, Tianfan, Cao Xiao, Cheng Qian, Lucas M. Glass, and Jimeng Sun. 2021. “Probabilistic and Dynamic Molecule-Disease Interaction Modeling for Drug Discovery.” In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 404–14. KDD ’21.
  • Fu, Tianfan, Kexin Huang, Cao Xiao, Lucas M. Glass, and Jimeng Sun. 2022. “HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data.” Cell Patterns and also at arXiv [cs.CY]. arXiv. http://arxiv.org/abs/2102.04252 .
  • Huang, Kexin, Cao Xiao, Lucas M. Glass, and Jimeng Sun. 2020. “MolTrans: Molecular Interaction Transformer for Drug–target Interaction Prediction.” Bioinformatics , October. https://doi.org/10.1093/bioinformatics/btaa880.

Section 7

Section 8

  • Y. Zhou, X. Li, and A. Banerjee, “Noisy Truncated SGD: Optimization and Generalization,” SIAM International Conference on Data Mining (SDM), 2022, https://arxiv.org/abs/2103.00075
  • M. Belkin, D. Hsu, S. Ma, S. Mandal, “Reconciling modern machine learning practice and the bias-variance trade-off,” Proceedings National Academy of Science (PNAS), 2019, https://www.pnas.org/content/116/32/15849.short

Section 9

Session 10