Sheshbolouki, A., & Ozsu, T. (2023). sGrow: Explaining the Scale-Invariant Strength Assortativity of Streaming Butterflies ACM Transactions on the Web, 17, 1-24. https://doi.org/10.1145/3572408
References
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2023
Ma, X., Teofili, T., & Lin, J. (2023). Anserini Gets Dense Retrieval: Integration of Lucene\textquoterights HNSW Indexes ArXiv, abs/2304.12139. https://doi.org/10.48550/arXiv.2304.12139
Lin, S.-C., & Lin, J. (2023). A Dense Representation Framework for Lexical and Semantic Matching ACM Transactions on Information Systems (TOIS), 41, 1-110. https://doi.org/10.1145/3582426
2022
Li, H., Wang, S., Zhuang, S., Mourad, A., Ma, X., Lin, J., & Zuccon, G. (2022). To Interpolate or Not to Interpolate: PRF, Dense and Sparse Retrievers ArXiv, abs/2205.00235. https://doi.org/10.48550/arXiv.2205.00235
Pacaci, A., Bonifati, A., & Ozsu, T. (2022). Evaluating Complex Queries on Streaming Graphs Presented at the Evaluating Complex Queries on Streaming Graphs conference. https://doi.org/10.1109/ICDE53745.2022.00025
Guo, R., Guo, V., Kim, A., Hildred, J., & Daudjee, K. (2022). Hydrozoa: Dynamic Hybrid-Parallel DNN Training on Serverless Containers Presented at the Hydrozoa: Dynamic Hybrid-Parallel DNN Training on Serverless Containers conference. Retrieved from https://proceedings.mlsys.org/paper/2022/hash/ea5d2f1c4608232e07d3aa3d998e5135-Abstract.html
Pappachan, P., Zhang, S., He, X., & Mehrotra, S. (2022). Don\textquoterightt Be a Tattle-Tale: Preventing Leakages Through Data Dependencies On Access Control Protected Data Proceedings of the VLDB Endowment (PVLDB), 15, 2437-2449. Retrieved from https://www.vldb.org/pvldb/vol15/p2437-pappachan.pdf
Karegar, R., Mirsafian, M., Godfrey, P., Golab, L., Kargar, M., Srivastava, D., & Szlichta, J. (2022). Discovering Domain Orders via Order Dependencies Presented at the Discovering Domain Orders via Order Dependencies conference. https://doi.org/10.1109/ICDE53745.2022.00087
Lin, S.-C., Li, M., & Lin, J. (2022). Aggretriever: A Simple Approach to Aggregate Textual Representation For Robust Dense Passage Retrieval ArXiv, abs/2208.00511. https://doi.org/10.48550/arXiv.2208.00511
Seltzer, J., Cheng, K., Zong, S., & Lin, J. (2022). Flipping the Script: Inverse Information Seeking Dialogues for Market Research Presented at the Flipping the Script: Inverse Information Seeking Dialogues for Market Research conference. https://doi.org/10.1145/3477495.3536326