Strategic Network Formation with Attack and Immunization von Goyal, Sanjeev, Jabbari, Shahin, Kearns, Michael, Khanna, Sanjeev, Morgenstern, Jamie

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Learning What’s Going on: Reconstructing Preferences and Priorities from Opaque Transactions von Blum, Avrim, Mansour, Yishay, Morgenstern, Jamie

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Private Pareto Optimal Exchange von Kannan, Sampath, Morgenstern, Jamie, Rogers, Ryan, Roth, Aaron

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Competition Alleviates Present Bias in Task Completion von Saraf, Aditya, Karlin, Anna R., Morgenstern, Jamie

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Preference Dynamics Under Personalized Recommendations von Dean, Sarah, Morgenstern, Jamie

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Auctions and Peer Prediction for Academic Peer Review von Srinivasan, Siddarth, Morgenstern, Jamie

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Large language models should not replace human participants because they can misportray and flatten identity groups von Wang, Angelina, Morgenstern, Jamie, Dickerson, John P

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Who's in and who's out? A case study of multimodal CLIP-filtering in DataComp von Hong, Rachel, Agnew, William, Kohno, Tadayoshi, Morgenstern, Jamie

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Fair Clustering: Critique, Caveats, and Future Directions von Dickerson, John, Esmaeili, Seyed A, Morgenstern, Jamie, Zhang, Claire Jie

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Auctions and Peer Prediction for Academic Peer Review von Srinivasan, Siddarth, Morgenstern, Jamie

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Fair Active Learning in Low-Data Regimes von Camilleri, Romain, Wagenmaker, Andrew, Morgenstern, Jamie, Jain, Lalit, Jamieson, Kevin

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Distributionally Robust Data Join von Awasthi, Pranjal, Jung, Christopher, Morgenstern, Jamie

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Optimal Spend Rate Estimation and Pacing for Ad Campaigns with Budgets von Kumar, Bhuvesh, Morgenstern, Jamie, Schrijvers, Okke

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Competition Alleviates Present Bias in Task Completion von Saraf, Aditya, Karlin, Anna R, Morgenstern, Jamie

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Doubly Constrained Fair Clustering von Dickerson, John, Esmaeili, Seyed A, Morgenstern, Jamie, Zhang, Claire Jie

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Preference Dynamics Under Personalized Recommendations von Dean, Sarah, Morgenstern, Jamie

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Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable von Bertran, Martin, Tang, Shuai, Kearns, Michael, Morgenstern, Jamie, Roth, Aaron, Wu, Zhiwei Steven

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Active Learning with Safety Constraints von Camilleri, Romain, Wagenmaker, Andrew, Morgenstern, Jamie, Jain, Lalit, Jamieson, Kevin

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Initializing Services in Interactive ML Systems for Diverse Users von Bose, Avinandan, Curmei, Mihaela, Jiang, Daniel L, Morgenstern, Jamie, Dean, Sarah, Ratliff, Lillian J, Fazel, Maryam

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A Notion of Individual Fairness for Clustering von Kleindessner, Matthäus, Awasthi, Pranjal, Morgenstern, Jamie

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