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cs.LG2026
Learning to Sparsify Stochastic Linear Bandits
Zhengmiao Wang, Ming Chi, Zhi-Wei Liu +2
This paper addresses the problem of learning to sparsify stochastic linear bandits, where a decision-maker sequentially selects actions from a high-dimensional space subject to a s…
cs.LG2026
Balancing Privacy-Quality-Efficiency in Federated Learning through Round-Based Interleaving of Protection Techniques
Yenan Wang, Carla Fabiana Chiasserini, Elad Michael Schiller
In federated learning (FL), balancing privacy protection, learning quality, and efficiency remains a challenge. Privacy protection mechanisms, such as Differential Privacy (DP), de…
cs.LG2024
Edge-Assisted ML-Aided Uncertainty-Aware Vehicle Collision Avoidance at Urban Intersections
Dinesh Cyril Selvaraj, Christian Vitale, Tania Panayiotou +3
Intersection crossing represents one of the most dangerous sections of the road infrastructure and Connected Vehicles (CVs) can serve as a revolutionary solution to the problem. In…