| PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferences D Chen, Y Chen, A Rege, RK Vinayak arXiv preprint arXiv:2406.08469, 2024 | 4 | 2024 |
| Crowdsourced Clustering via Active Querying: Practical Algorithm with Theoretical Guarantees Y Chen, RK Vinayak, B Hassibi Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 11 …, 2023 | 4 | 2023 |
| Learning populations of preferences via pairwise comparison queries G Tatli, Y Chen, RK Vinayak International Conference on Artificial Intelligence and Statistics, 1720-1728, 2024 | 3 | 2024 |
| Pearls from Pebbles: Improved Confidence Functions for Auto-labeling H Vishwakarma, SJ Tay, SSS Namburi, F Sala, RK Vinayak arXiv preprint arXiv:2404.16188, 2024 | 1 | 2024 |
| PabLO: Improving Semi-Supervised Learning with Pseudolabeling Optimization H Vishwakarma, Y Chen, SSS Namburi, SJ Tay, RK Vinayak, F Sala | | 2024 |
| Query Design for Crowdsourced Clustering: Effect of Cognitive Overload and Contextual Bias Y Chen, RK Vinayak ICML 2024 Workshop on Models of Human Feedback for AI Alignment, 0 | | |
| Modeling the Plurality of Human Preferences via Ideal Points D Chen, Y Chen, A Rege, RK Vinayak ICML 2024 Workshop on Models of Human Feedback for AI Alignment, 0 | | |
| Crowdsourced clustering via active querying Y Chen, RK Vinayak, B Hassibi | | |
| Learning Preference Distributions From Pairwise Comparisons G Tatli, Y Chen, RK Vinayak | | |
Ramya Korlakai VinayakAssistant Professor, UW-MadisonVerified email at ece.wisc.edu
