Ilyas, I. ., Rekatsinas, T. ., Konda, V. ., Pound, J. ., Qi, X. ., & Soliman, M. A. (2022). Saga: A Platform for Continuous Construction and Serving of Knowledge At Scale. Saga: A Platform for Continuous Construction and Serving of Knowledge At Scale. Presented at the. https://doi.org/10.1145/3514221.3526049
Publications
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Borgida, A. ., Franconi, E. ., Toman, D. ., & Weddell, G. . (2022). Understanding Document Data Sources Using Ontologies With Referring Expressions. Understanding Document Data Sources Using Ontologies With Referring Expressions Primary Tabs View. Presented at the. https://doi.org/10.1007/978-3-031-22695-3_26
Ilyas, I. ., & Rekatsinas, T. . (2022). Machine Learning and Data Cleaning: Which Serves the Other?. Journal of Data and Information Quality, 14, 1-13. https://doi.org/10.1145/3506712
Nanayakkara, P. ., Bater, J. ., He, X. ., Hullman, J. ., & Rogers, J. . (2022). Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases. ArXiv, abs/2201.05964. Retrieved from https://arxiv.org/abs/2201.05964
Thakur, N. ., Reimers, N. ., & Lin, J. . (2022). Domain Adaptation for Memory-Efficient Dense Retrieval. ArXiv, abs/2205.11498. https://doi.org/10.48550/arXiv.2205.11498
Trotman, A. ., Mackenzie, J. ., Parameswaran, P. ., & Lin, J. . (2022). A Common Framework for Exploring Document-at-a-Time and Score-at-a-Time Retrieval Methods. A Common Framework for Exploring Document-at-a-Time and Score-at-a-Time Retrieval Methods. Presented at the. https://doi.org/10.1145/3477495.3531657
Zhong, Y. ., Xiao, J. ., Vetterli, T. ., Matin, M. ., Loo, E. ., Lin, J. ., Bourgon, R. ., & Shapira, O. . (2022). Improving Precancerous Case Characterization via Transformer-Based Ensemble Learning. Improving Precancerous Case Characterization via Transformer-Based Ensemble Learning. Presented at the. Retrieved from https://aclanthology.org/2022.emnlp-industry.38
Ilyas, I. ., & Naumann, F. . (2022). Data Errors: Symptoms, Causes and Origins. IEEE Data Engineering Bulletin, 45, 4-9. Retrieved from http://sites.computer.org/debull/A22mar/p4.pdf
Yan, D. ., Guo, G. ., Khalil, J. ., Ozsu, T. ., Ku, W.-S. ., & Lui, J. C. S. (2022). G-Thinker: A General Distributed Framework for Finding Qualified Subgraphs In a Big Graph With Load Balancing. The VLDB Journal, 31, 287-320. https://doi.org/10.1007/s00778-021-00688-z
Liu, Y. ., Hu, C. ., & Lin, J. . (2022). Another Look at Information Retrieval as Statistical Translation. Another Look at Information Retrieval As Statistical Translation. Presented at the. https://doi.org/10.1145/3477495.3531717