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cs.LG2025
Optimistic Gradient Learning with Hessian Corrections for High-Dimensional Black-Box Optimization
Yedidya Kfir, Elad Sarafian, Sarit Kraus +1
Black-box algorithms are designed to optimize functions without relying on their underlying analytical structure or gradient information, making them essential when gradients are i…
cs.LG2024
Contrastive Explainable Clustering with Differential Privacy
Dung Nguyen, Ariel Vetzler, Sarit Kraus +1
This paper presents a novel approach to Explainable AI (XAI) that combines contrastive explanations with differential privacy for clustering algorithms. Focusing on k-median and k-…
cs.LG2024★ 3 cited
Intelligent Agents for Auction-based Federated Learning: A Survey
Xiaoli Tang, Han Yu, Xiaoxiao Li +1
Auction-based federated learning (AFL) is an important emerging category of FL incentive mechanism design, due to its ability to fairly and efficiently motivate high-quality data o…