3 papers
cs.CG2026
Almost-Optimal Upper and Lower Bounds for Clustering in Low Dimensional Euclidean Spaces
Vincent Cohen-Addad, Karthik C. S., David Saulpic +1
The -median and -means clustering objectives are classic objectives for modeling clustering in a metric space. Given a set of points in a metric space, the goal of the -me…
cs.LG2025
Federated Learning in Practice: Reflections and Projections
Katharine Daly, Hubert Eichner, Peter Kairouz +3
Federated Learning (FL) is a machine learning technique that enables multiple entities to collaboratively learn a shared model without exchanging their local data. Over the past de…
cs.GT2024
Relying on the Metrics of Evaluated Agents
Serena Wang, Michael I. Jordan, Katrina Ligett +1
Online platforms and regulators face a continuing problem of designing effective evaluation metrics. While tools for collecting and processing data continue to progress, this has n…