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Mahmoud F. Sayed
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Journal Articles
- 2022
- [j3]Jason R. Baron, Mahmoud F. Sayed, Douglas W. Oard
:
Providing More Efficient Access to Government Records: A Use Case Involving Application of Machine Learning to Improve FOIA Review for the Deliberative Process Privilege. ACM Journal on Computing and Cultural Heritage 15(1): 5:1-5:19 (2022) - 2021
- [j2]Modassir Iqbal, Katie Shilton, Mahmoud F. Sayed, Douglas W. Oard
, Jonah Lynn Rivera, William Cox:
Search with Discretion: Value Sensitive Design of Training Data for Information Retrieval. Proc. ACM Hum. Comput. Interact. 5(CSCW1): 133:1-133:20 (2021) - 2019
- [j1]Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, Michael D. Ekstrand, Adam Roegiest, Aldo Lipani
, Alex Beutel, Ana Lucic, Ana-Andreea Stoica, Anubrata Das, Asia Biega, Bart Voorn, Claudia Hauff, Damiano Spina, David D. Lewis, Douglas W. Oard, Emine Yilmaz, Faegheh Hasibi, Gabriella Kazai, Graham McDonald, Hinda Haned, Iadh Ounis, Ilse van der Linden, Joris Baan, Kamuela N. Lau, Krisztian Balog, Mahmoud F. Sayed, Maria Panteli, Mark Sanderson, Matthew Lease, Preethi Lahoti, Toshihiro Kamishima:
FACTS-IR: fairness, accountability, confidentiality, transparency, and safety in information retrieval. SIGIR Forum 53(2): 20-43 (2019)
Conference and Workshop Papers
- 2022
- [c5]Mahmoud F. Sayed, Nishanth Mallekav, Douglas W. Oard
:
Comparing Intrinsic and Extrinsic Evaluation of Sensitivity Classification. ECIR (2) 2022: 215-222 - 2020
- [c4]Mahmoud F. Sayed, William Cox, Jonah Lynn Rivera, Caitlin Christian-Lamb
, Modassir Iqbal, Douglas W. Oard
, Katie Shilton:
A Test Collection for Relevance and Sensitivity. SIGIR 2020: 1605-1608 - [c3]Mahmoud F. Sayed, Douglas W. Oard:
The University of Maryland at the TREC 2020 Fair Ranking Track. TREC 2020 - 2019
- [c2]Mahmoud F. Sayed, Douglas W. Oard
:
Jointly Modeling Relevance and Sensitivity for Search Among Sensitive Content. SIGIR 2019: 615-624 - 2014
- [c1]Ahmed E. Kosba, Dimitrios Papadopoulos, Charalampos Papamanthou, Mahmoud F. Sayed, Elaine Shi, Nikos Triandopoulos:
TRUESET: Faster Verifiable Set Computations. USENIX Security Symposium 2014: 765-780
Informal and Other Publications
- 2020
- [i2]Jason R. Baron, Mahmoud F. Sayed, Douglas W. Oard:
Providing More Efficient Access To Government Records: A Use Case Involving Application of Machine Learning to Improve FOIA Review for the Deliberative Process Privilege. CoRR abs/2011.07203 (2020) - 2014
- [i1]Ahmed E. Kosba, Dimitrios Papadopoulos, Charalampos Papamanthou, Mahmoud F. Sayed, Elaine Shi, Nikos Triandopoulos:
TRUESET: Nearly Practical Verifiable Set Computations. IACR Cryptol. ePrint Arch. 2014: 160 (2014)
Coauthor Index
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