4 citations · 10 across the 11 of their papers we have counts for
3 papers · 1 filter
Submodular Maximization Approaches for Equitable Client Selection in Federated Learning
Andrés Catalino Castillo Jiménez, Ege C. Kaya, Lintao Ye +1
In a conventional Federated Learning framework, client selection for training typically involves the random sampling of a subset of clients in each iteration. However, this random…
Localized Distributional Robustness in Submodular Multi-Task Subset Selection
Ege C. Kaya, Abolfazl Hashemi
In this work, we treat the problem of multi-task submodular optimization from the perspective of local distributional robustness within the neighborhood of a reference distribution…
Randomized Greedy Methods for Weak Submodular Sensor Selection with Robustness Considerations
Ege C. Kaya, Michael Hibbard, Takashi Tanaka +2
We study a pair of budget- and performance-constrained weak-submodular maximization problems. For computational efficiency, we explore the use of stochastic greedy algorithms which…