10 citations · 20 across the 4 of their papers we have counts for
3 papers · 1 filter
Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping
Umut Şimşekli, Mert Gürbüzbalaban, Sinan Yıldırım +1
The injection of heavy-tailed noise into the iterates of stochastic gradient descent (SGD) has garnered growing interest in recent years due to its theoretical and empirical benefi…
Generalization Bounds with Data-dependent Fractal Dimensions
Benjamin Dupuis, George Deligiannidis, Umut Şimşekli
Providing generalization guarantees for modern neural networks has been a crucial task in statistical learning. Recently, several studies have attempted to analyze the generalizati…
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms
Alexander Camuto, George Deligiannidis, Murat A. Erdogdu +3
Understanding generalization in deep learning has been one of the major challenges in statistical learning theory over the last decade. While recent work has illustrated that the d…