Analyzing Personality through Social Media Profile Picture Choice L Liu, D Preotiuc-Pietro, ZR Samani, ME Moghaddam, LH Ungar ICWSM, 211-220, 2016 | 363 | 2016 |
Off-policy risk assessment in contextual bandits A Huang, L Leqi, Z Lipton, K Azizzadenesheli Advances in Neural Information Processing Systems 34, 23714-23726, 2021 | 35 | 2021 |
Action-sufficient state representation learning for control with structural constraints B Huang, C Lu, L Leqi, JM Hernández-Lobato, C Glymour, B Schölkopf, ... International Conference on Machine Learning, 9260-9279, 2022 | 32 | 2022 |
Rebounding Bandits for Modeling Satiation Effects L Leqi, F Kilinc Karzan, Z Lipton, A Montgomery Advances in Neural Information Processing Systems 34, 2021 | 30 | 2021 |
A Taxonomy of Human and ML Strengths in Decision-Making to Investigate Human-ML Complementarity C Rastogi, L Leqi, K Holstein, H Heidari Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 11 …, 2023 | 29* | 2023 |
Uniform convergence of rank-weighted learning J Khim, L Leqi, A Prasad, P Ravikumar International Conference on Machine Learning, 5254-5263, 2020 | 26 | 2020 |
On Human-Aligned Risk Minimization L Leqi, A Prasad, PK Ravikumar Advances in Neural Information Processing Systems, 15055-15064, 2019 | 25 | 2019 |
On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk A Huang, L Leqi, ZC Lipton, K Azizzadenesheli arXiv preprint arXiv:2103.02827, 2021 | 17 | 2021 |
Modeling attrition in recommender systems with departing bandits O Ben-Porat, L Cohen, L Leqi, ZC Lipton, Y Mansour Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6072-6079, 2022 | 14 | 2022 |
Personalized Language Modeling from Personalized Human Feedback X Li, ZC Lipton, L Leqi arXiv preprint arXiv:2402.05133, 2024 | 13 | 2024 |
Median Optimal Treatment Regimes L Leqi, EH Kennedy arXiv preprint arXiv:2103.01802, 2021 | 12 | 2021 |
Supervised Learning with General Risk Functionals L Leqi, A Huang, Z Lipton, K Azizzadenesheli International Conference on Machine Learning, 12570-12592, 2022 | 10 | 2022 |
A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits L Leqi, G Zhou, F Kilinc-Karzan, Z Lipton, A Montgomery Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems …, 2023 | 6 | 2023 |
Accounting for AI and Users Shaping One Another: The Role of Mathematical Models S Dean, E Dong, M Jagadeesan, L Leqi arXiv preprint arXiv:2404.12366, 2024 | 5* | 2024 |
Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework J Li, Z Tang, X Liu, P Spirtes, K Zhang, L Leqi, Y Liu arXiv preprint arXiv:2403.08743, 2024 | 5 | 2024 |
Off-Policy Risk Assessment for Markov Decision Processes A Huang, L Leqi, Z Lipton, K Azizzadenesheli International Conference on Artificial Intelligence and Statistics, 5022-5050, 2022 | 5 | 2022 |
Counterfactual Metrics for Auditing Black-Box Recommender Systems for Ethical Concerns NJ Akpinar, L Leqi, D Hadfield-Menell, Z Lipton Workshop on Responsible Decision Making in Dynamic Environments …, 2022 | 5 | 2022 |
The sample complexity of semi-supervised learning with nonparametric mixture models C Dan, L Leqi, B Aragam, PK Ravikumar, EP Xing Advances in Neural Information Processing Systems 31, 2018 | 5 | 2018 |
Automated Dependence Plots D Inouye, L Leqi, JS Kim, B Aragam, P Ravikumar Conference on Uncertainty in Artificial Intelligence, 1238-1247, 2020 | 4 | 2020 |
Engineering a Safer Recommender System L Leqi, S Dean Workshop on Responsible Decision Making in Dynamic Environments, 2022 | 3 | 2022 |