| Probabilistic fair clustering S Esmaeili, B Brubach, L Tsepenekas, J Dickerson Advances in Neural Information Processing Systems 33, 12743-12755, 2020 | 43 | 2020 |
| A pairwise fair and community-preserving approach to k-center clustering B Brubach, D Chakrabarti, J Dickerson, S Khuller, A Srinivasan, ... International conference on machine learning, 1178-1189, 2020 | 41 | 2020 |
| Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints B Brubach, D Chakrabarti, JP Dickerson, A Srinivasan, L Tsepenekas Proc. Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021 | 28 | 2021 |
| A New Notion of Individually Fair Clustering: -Equitable -Center D Chakrabarti, JP Dickerson, SA Esmaeili, A Srinivasan, L Tsepenekas International conference on artificial intelligence and statistics, 6387-6408, 2022 | 25 | 2022 |
| A unified approach to online matching with conflict-aware constraints P Xu, Y Shi, H Cheng, J Dickerson, KA Sankararaman, A Srinivasan, ... Proceedings of the AAAI conference on artificial intelligence 33 (01), 2221-2228, 2019 | 18 | 2019 |
| Fair disaster containment via graph-cut problems M Dinitz, A Srinivasan, L Tsepenekas, A Vullikanti International Conference on Artificial Intelligence and Statistics, 6321-6333, 2022 | 9* | 2022 |
| Controlling epidemic spread using probabilistic diffusion models on networks AE Babay, M Dinitz, A Srinivasan, L Tsepenekas, A Vullikanti International Conference on Artificial Intelligence and Statistics, 11641-11654, 2022 | 6 | 2022 |
| Deploying vaccine distribution sites for improved accessibility and equity to support pandemic response GZ Li, A Li, M Marathe, A Srinivasan, L Tsepenekas, A Vullikanti Autonomous Agents and Multi-Agent Systems 37 (2), 31, 2023 | 5 | 2023 |
| Fairness in Clustering B Brubach, D Chakrabarty, JP Dickerson, S Esmaeili, M Kleindessner, ... | 3* | 2022 |
| Approximating Two-Stage Stochastic Supplier Problems B Brubach, N Grammel, DG Harris, A Srinivasan, L Tsepenekas, ... Approximation, Randomization, and Combinatorial Optimization. Algorithms and …, 2020 | 3 | 2020 |
| Message Routing In Wireless and Mobile Networks Using TDMA Technology T Aslanidis, L Tsepenekas arXiv preprint arXiv:1607.00604, 2016 | 3 | 2016 |
| Comparing apples to oranges: learning similarity functions for data produced by different distributions L Tsepenekas, I Brugere, F Lecue, D Magazzeni Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Improving Scheduling of Data Transmission in TDMA Systems T Aslanidis, L Tsepenekas Fourth International Conference of Networks and Communications, Sydney …, 2016 | 1 | 2016 |
| System, method, and computer program for computing data contraction and similarity from heterogeneous data descriptors L Tsepenekas, I Brugere, F Lecue, D Magazzeni US Patent App. 18/112,341, 2024 | | 2024 |
| SHAP@ k: Efficient and Probably Approximately Correct (PAC) Identification of Top-k Features S Kariyappa, L Tsepenekas, F Lécué, D Magazzeni Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), 13068 …, 2024 | | 2024 |
| Stochastic Optimization and Learning for Two-Stage Supplier Problems B Brubach, N Grammel, DG Harris, A Srinivasan, L Tsepenekas, ... ACM Transactions on Probabilistic Machine Learning, 2024 | | 2024 |
| Efficient and equitable deployment of mobile vaccine distribution centers DQ Chen, A Li, G Li, M Marathe, A Srinivasan, L Tsepenekas, A Vullikanti Proc. International Joint Conference on Artificial Intelligence (IJCAI), 2023 | | 2023 |
| On Algorithmic Fairness and Stochastic Models for Combinatorial Optimization and Unsupervised Machine Learning L Tsepenekas University of Maryland, College Park, 2022 | | 2022 |
