7 citations · 16 across the 9 of their papers we have counts for
4 papers · 1 filter
Federated Learning Under Restricted User Availability
Periklis Theodoropoulos, Konstantinos E. Nikolakakis, Dionysis Kalogerias
Federated Learning (FL) is a decentralized machine learning framework that enables collaborative model training while respecting data privacy. In various applications, non-uniform…
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning
Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos +5
Methods for carefully selecting or generating a small set of training data to learn from, i.e., data pruning, coreset selection, and data distillation, have been shown to be effect…
Select without Fear: Almost All Mini-Batch Schedules Generalize Optimally
Konstantinos E. Nikolakakis, Amin Karbasi, Dionysis Kalogerias
We establish matching upper and lower generalization error bounds for mini-batch Gradient Descent (GD) training with either deterministic or stochastic, data-independent, but other…
Black-Box Generalization: Stability of Zeroth-Order Learning
Konstantinos E. Nikolakakis, Farzin Haddadpour, Dionysios S. Kalogerias +1
We provide the first generalization error analysis for black-box learning through derivative-free optimization. Under the assumption of a Lipschitz and smooth unknown loss, we cons…