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cs.LG2023
LiveTune: Dynamic Parameter Tuning for Feedback-Driven Optimization
Soheil Zibakhsh Shabgahi, Nojan Sheybani, Aiden Tabrizi +1
Feedback-driven optimization, such as traditional machine learning training, is a static process that lacks real-time adaptability of hyperparameters. Tuning solutions for optimiza…
cs.LG2022
zPROBE: Zero Peek Robustness Checks for Federated Learning
Zahra Ghodsi, Mojan Javaheripi, Nojan Sheybani +3
Privacy-preserving federated learning allows multiple users to jointly train a model with coordination of a central server. The server only learns the final aggregation result, thu…