Title |
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 Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping UsersACM Conference on Recommender Systems (RecSys), 2025 |
 Enhancing New-item Fairness in Dynamic Recommender SystemsAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2025 |
 Joint Optimal Transport and Embedding for Network AlignmentThe Web Conference (WWW), 2025 |
 How Efficient is LLM-Generated Code? A Rigorous & High-Standard BenchmarkInternational Conference on Learning Representations (ICLR), 2024 |
 Fairness-Aware Graph Neural Networks: A SurveyACM Transactions on Knowledge Discovery from Data (TKDD), 2023 April Chen Ryan Rossi Namyong Park Puja Trivedi Yu Wang Tong Yu Sungchul Kim Franck Dernoncourt Nesreen K. Ahmed |
 Joint Multisided Exposure Fairness for RecommendationAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022 |
 Meta-Learning for Online Update of Recommender SystemsAAAI Conference on Artificial Intelligence (AAAI), 2022 |
 Two-sided fairness in rankings via Lorenz dominanceNeural Information Processing Systems (NeurIPS), 2021 |
 Personalized Counterfactual Fairness in RecommendationAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021 |
 User-oriented Fairness in RecommendationThe Web Conference (WWW), 2021 |
 TFROM: A Two-sided Fairness-Aware Recommendation Model for Both
Customers and ProvidersAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021 |
 A Survey of Machine Learning for Computer Architecture and SystemsACM Computing Surveys (CSUR), 2021 |
 Fairness-Aware Explainable Recommendation over Knowledge GraphsAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020 |
 Controlling Fairness and Bias in Dynamic Learning-to-RankAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020 |
 Privacy-Aware Recommendation with Private-Attribute Protection using
Adversarial LearningWeb Search and Data Mining (WSDM), 2019 |
 Meta-Learning with Implicit GradientsNeural Information Processing Systems (NeurIPS), 2019 |
 Sequential Scenario-Specific Meta Learner for Online RecommendationKnowledge Discovery and Data Mining (KDD), 2019 |
 Stochastic Optimization of Sorting Networks via Continuous RelaxationsInternational Conference on Learning Representations (ICLR), 2019 |
 SQL-Rank: A Listwise Approach to Collaborative RankingInternational Conference on Machine Learning (ICML), 2018 |
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 Adam: A Method for Stochastic OptimizationInternational Conference on Learning Representations (ICLR), 2014 Diederik P. Kingma Jimmy Ba |
 BPR: Bayesian Personalized Ranking from Implicit FeedbackConference on Uncertainty in Artificial Intelligence (UAI), 2009 |
 Domain Adaptation: Learning Bounds and AlgorithmsAnnual Conference Computational Learning Theory (COLT), 2009 |
