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20212026
most citedQuPeD: Quantized Personalization via Distillation with Applications to Federated Learning

5 citations · 10 across the 10 of their papers we have counts for

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cs.LG2024

ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning

Kaan Ozkara, Bruce Huang, Ruida Zhou +1

Statistical heterogeneity of clients' local data is an important characteristic in federated learning, motivating personalized algorithms tailored to the local data statistics. Tho…

cs.LG2024

MADA: Meta-Adaptive Optimizers through hyper-gradient Descent

Kaan Ozkara, Can Karakus, Parameswaran Raman +4

Following the introduction of Adam, several novel adaptive optimizers for deep learning have been proposed. These optimizers typically excel in some tasks but may not outperform Ad…