Tsepenekas, Leonidas

10 publications

AAAI 2024 SHAP@k: Efficient and Probably Approximately Correct (PAC) Identification of Top-K Features Sanjay Kariyappa, Leonidas Tsepenekas, Freddy Lécué, Daniele Magazzeni

NeurIPS 2023 Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions Leonidas Tsepenekas, Ivan Brugere, Freddy Lecue, Daniele Magazzeni

IJCAI 2023 Efficient and Equitable Deployment of Mobile Vaccine Distribution Centers Da Qi Chen, Ann Li, George Z. Li, Madhav V. Marathe, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti

AISTATS 2022 A New Notion of Individually Fair Clustering: $α$-Equitable $k$-Center Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas

AISTATS 2022 Controlling Epidemic Spread Using Probabilistic Diffusion Models on Networks Amy E. Babay, Michael Dinitz, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti

AISTATS 2022 Fair Disaster Containment via Graph-Cut Problems Michael Dinitz, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti

AAAI 2021 Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas

ICML 2020 A Pairwise Fair and Community-Preserving Approach to K-Center Clustering Brian Brubach, Darshan Chakrabarti, John Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas

NeurIPS 2020 Probabilistic Fair Clustering Seyed Esmaeili, Brian Brubach, Leonidas Tsepenekas, John Dickerson

AAAI 2019 A Unified Approach to Online Matching with Conflict-Aware Constraints Pan Xu, Yexuan Shi, Hao Cheng, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yongxin Tong, Leonidas Tsepenekas