Author

Muzaffer Citir

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#machine learning Preprint Sep 2026

Client and Training Data Selection for Computationally Efficient Synchronized Federated Learning

Federated learning (FL) is a promising paradigm of machine learning, which preserves user privacy by enabling learning without sharing raw data with a cloud server. Straggling clients have been a problem for FL as they introduce delays in aggregating the local models and hence, the convergence of the global model. Ther...

Muzaffer Citir, Hiroki Nishikawa, Sangyoung Park · 0 citations

Open access Aug 2026

Infrastructure-Scheduled In-Vehicle Auditory Signals for Manual Driving Coordination in V2I Mixed Traffic

This work proposes a framework in which infrastructure communicates its trajectory planning to HD vehicles via designed in-vehicle auditory signals, and demonstrates the feasibility of the proposed platform and its potential as a quantitative environment for infrastructure-based interventions in mixed traffic.

Kyoko Takii, Fuma Sawa, Sangyoung Park et al. · ACM Journal on Autonomous Tr... · 0 citations