Jeffrey Chan

Publications
Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan (2026). Diversity-Augmented Negative Sampling for Implicit Collaborative Filtering. Proceedings of the ACM Web Conference 2026, WWW 2026, Dubai, United Arab Emirates, originally scheduled for April 13-17, 2026, rescheduled for June 29 - July 3, 2026.
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Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan (2025). Diverse Negative Sampling for Implicit Collaborative Filtering. CoRR.
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Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan (2025). Evaluating and Addressing Fairness Across User Groups in Negative Sampling for Recommender Systems. Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025.
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Edward A. Small, Wei Shao, Zeliang Zhang, Peihan Liu, Jeffrey Chan, Kacper Sokol, Flora D. Salim (2025). How robust is your fair model? Exploring the robustness of prominent fairness strategies. Data Min. Knowl. Discov..
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Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan (2025). Leveraging Complementary AI Explanations to Mitigate Misunderstanding in XAI. IEEE Swiss Conference on Data Science, SDS 2025, Zürich, Switzerland, June 26-27, 2025.
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Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan (2025). Leveraging Complementary AI Explanations to Mitigate Misunderstanding in XAI. CoRR.
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Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan (2025). Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse. Mach. Learn..
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Edward Small, Kacper Sokol, Daniel Manning, Flora D. Salim, Jeffrey Chan (2024). Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness. The 2024 ACM Conference on Fairness, Accountability, and Transparency, FAccT 2024, Rio de Janeiro, Brazil, June 3-6, 2024.
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Yueqing Xuan, Kacper Sokol, Mark Sanderson, Jeffrey Chan (2024). Perfect Counterfactuals in Imperfect Worlds: Modelling Noisy Implementation of Actions in Sequential Algorithmic Recourse. CoRR.
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Edward A. Small, Jeffrey N. Clark, Christopher J. McWilliams, Kacper Sokol, Jeffrey Chan, Flora D. Salim, Raúl Santos-Rodríguez (2023). Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse. CoRR.
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Edward A. Small, Kacper Sokol, Daniel Manning, Flora D. Salim, Jeffrey Chan (2023). Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness. CoRR.
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Yueqing Xuan, Kacper Sokol, Jeffrey Chan, Mark Sanderson (2023). More Is Less: When Do Recommenders Underperform for Data-rich Users?. CoRR.
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Dilini Rajapaksha, Kacper Sokol, Jeffrey Chan, Flora D. Salim, Mukesh Prasad, Mahendra Samarawickrama (2022). Analysing Donors' Behaviour in Non-profit Organisations for Disaster Resilience: The 2019-2020 Australian Bushfires Case Study. CoRR.
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Kacper Sokol, Meelis Kull, Jeffrey Chan, Flora Dilys Salim (2022). Ethical and Fairness Implications of Model Multiplicity. CoRR.
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Edward Small, Wei Shao, Zeliang Zhang, Peihan Liu, Jeffrey Chan, Kacper Sokol, Flora D. Salim (2022). How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies. CoRR.
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