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Recommended citation: D. Liu and S. Sakha. A New AI Lexicon: Power. 2021. An essay contribution to AI Now's AI Lexicon project.
Recommended citation: C. Conti-Cook, R. Pakzad, S. A. Sakha, and D. Liu. A Guiding Framework for Vetting Technology Vendors Operating in the Public Sector. 2023. A research report by the Ford Foundation.
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Recommended citation: D. Liu, J. Baek, T. Eliassi-Rad. 2023. When Collaborative Filtering is not Collaborative: Unfairness of PCA for Recommendations. https://arxiv.org/abs/2310.09687
Recommended citation: D. Liu, A. Seshadri, T. Eliassi-Rad, J. Ugander. 2024. Re-visiting Skip-Gram Negative Sampling: Dimension Regularization for More Efficient Dissimilarity Preservation in Graph Embeddings. https://arxiv.org/abs/2405.00172
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Recommended citation: D. Liu and M. Salganik. Successes and struggles with computational reproducibility: Lessons from the Fragile Families Challenge. Socius 5, (2019): 1-21. https://journals.sagepub.com/doi/10.1177/2378023119849803
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Recommended citation: D. Liu, Z. Shafi, W. Fleisher, T. Eliassi-Rad, and S. Alfeld. RAWLSNET: Altering Bayesian Networks to Encode Rawlsian Fair Equality of Opportunity. AIES'21. https://dl.acm.org/doi/10.1145/3461702.3462618
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Recommended citation: D. Liu*, P. Nanayakkara*, S. Sakha, G. Abuhamad, S.L. Blodgett, N. Diakopoulos, J. Hullman, and T. Eliassi-Rad. Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews. AIES'22. https://dl.acm.org/doi/10.1145/3514094.3534155
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Recommended citation: A. Rissaki*, B. Scarone*, D. Liu, A. Pandey, B. Klein, T. Eliassi-Rad, and M.A. Borkin. 2022. BiaScope: Visual Unfairness Diagnosis for Graph Embeddings. Symposium on Visualization in Data Science at IEEE VIS (VDS '22). https://ieeexplore.ieee.org/document/9980579
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Recommended citation: D. Liu and T. Eliassi-Rad. 2023. Identifying and Mitigating Instability in Embeddings of the Degenerate Core. SIAM SDM'23. /files/papers/stable/stable-Main-SDM-23.pdf
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Recommended citation: D. Liu, V. Do, N. Usunier, M. Nickel. 2023. Group fairness without demographics using social networks. FAccT'23. https://arxiv.org/abs/2305.11361
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.
Recommended citation: Liu, D. M. 2018. Discovery Princeton's History: A textual analysis of collegiate newspaper headlines. B.S.E. Independent Work, Department of Computer Science, Princeton University, Princeton, NJ. http://dliu18.github.io/files/papers/digital_humanities.pdf
Recommended citation: Liu, D. M. 2018. Mining FERPA Notices for Texual Analysis of Education Privacy Policy. B.S.E. Independent Work, Department of Computer Science, Princeton University, Princeton, NJ. http://dliu18.github.io/files/papers/legal_nlp.pdf