| We need fairness and explainability in algorithmic hiring C Schumann, J Foster, N Mattei, J Dickerson International conference on autonomous agents and multi-agent systems (AAMAS), 2020 | 91 | 2020 |
| Measuring non-expert comprehension of machine learning fairness metrics D Saha, C Schumann, D Mcelfresh, J Dickerson, M Mazurek, M Tschantz International Conference on Machine Learning, 8377-8387, 2020 | 83 | 2020 |
| Transfer of machine learning fairness across domains C Schumann, X Wang, A Beutel, J Chen, H Qian, EH Chi arXiv preprint arXiv:1906.09688, 2019 | 64 | 2019 |
| A step toward more inclusive people annotations for fairness C Schumann, S Ricco, U Prabhu, V Ferrari, C Pantofaru Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 916-925, 2021 | 62 | 2021 |
| Group fairness in bandit arm selection C Schumann, Z Lang, N Mattei, JP Dickerson arXiv preprint arXiv:1912.03802, 2019 | 29 | 2019 |
| Which skin tone measures are the most inclusive? An investigation of skin tone measures for artificial intelligence CM Heldreth, EP Monk, AT Clark, C Schumann, X Eyee, S Ricco ACM Journal on Responsible Computing 1 (1), 1-21, 2024 | 25 | 2024 |
| Consensus and subjectivity of skin tone annotation for ML fairness C Schumann, F Olanubi, A Wright, E Monk, C Heldreth, S Ricco Advances in Neural Information Processing Systems 36, 30319-30348, 2023 | 25 | 2023 |
| The diverse cohort selection problem C Schumann, SN Counts, JS Foster, JP Dickerson arXiv preprint arXiv:1709.03441, 2017 | 25 | 2017 |
| Human comprehension of fairness in machine learning D Saha, C Schumann, DC McElfresh, JP Dickerson, ML Mazurek, ... Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 152-152, 2020 | 22 | 2020 |
| Imagen 3 J Baldridge, J Bauer, M Bhutani, N Brichtova, A Bunner, L Castrejon, ... arXiv preprint arXiv:2408.07009, 2024 | 20 | 2024 |
| Making the cut: A bandit-based approach to tiered interviewing C Schumann, Z Lang, J Foster, J Dickerson Advances in Neural Information Processing Systems 32, 2019 | 11 | 2019 |
| Group fairness in bandits with biased feedback C Schumann, Z Lang, N Mattei, JP Dickerson 21st International Conference on Autonomous Agents and Multiagent Systems …, 2022 | 6 | 2022 |
| The diverse cohort selection problem: Multi-armed bandits with varied pulls C Schumann, SN Counts, JS Foster, JP Dickerson CoRR, abs/1709.03441, 2017 | 4 | 2017 |
| What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models AI Humayun, I Amara, C Vasconcelos, D Ramachandran, C Schumann, ... arXiv preprint arXiv:2408.08307, 2024 | 2 | 2024 |
| Generalized people diversity: Learning a human perception-aligned diversity representation for people images H Srinivasan, C Schumann, A Sinha, D Madras, GO Olanubi, A Beutel, ... Proceedings of the 2024 ACM Conference on Fairness, Accountability, and …, 2024 | 1 | 2024 |
| On the local geometry of deep generative manifolds AI Humayun, I Amara, C Schumann, G Farnadi, N Rostamzadeh, ... ICML 2024 Workshop on Geometry-grounded Representation Learning and …, 2024 | 1 | 2024 |
| Exploring Diversity and Fairness in Machine Learning C Schumann University of Maryland, College Park, 2020 | 1 | 2020 |
| Understanding the Local Geometry of Generative Model Manifolds A Imtiaz Humayun, I Amara, C Schumann, G Farnadi, N Rostamzadeh, ... arXiv e-prints, arXiv: 2408.08307, 2024 | | 2024 |
| An approach to the fairy tale card game: a rotating sets competitive knapsack problem with strongly stochastic rewards and item availability C Schumann, T Highley, H Stickley Journal of Computing Sciences in Colleges 30 (3), 16-25, 2015 | | 2015 |
| What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models AI Humayun, I Amara, CN Vasconcelos, D Ramachandran, C Schumann, ... The Thirteenth International Conference on Learning Representations, 0 | | |
John P. DickersonAssociate Professor of Computer Science, University of Maryland & Chief Scientist, Arthur AIVerified email at cs.umd.edu