3 papers
cs.LG2025
Dynamic Algorithm for Explainable k-medians Clustering under lp Norm
Konstantin Makarychev, Ilias Papanikolaou, Liren Shan
We study the problem of explainable k-medians clustering introduced by Dasgupta, Frost, Moshkovitz, and Rashtchian (2020). In this problem, the goal is to construct a threshold dec…
cs.GT2025
Optimization of Scoring Rules
Jason D. Hartline, Yingkai Li, Liren Shan +1
We characterize the optimal reward functions (scoring rules) that incentivize an agent to acquire information and report it truthfully to the principal. The optimal scoring rules l…
cs.LG2025
LiD-FL: Towards List-Decodable Federated Learning
Hong Liu, Liren Shan, Han Bao +3
Federated learning is often used in environments with many unverified participants. Therefore, federated learning under adversarial attacks receives significant attention. This pap…