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stat.ML2026
Ratio-based Loss Functions
Lena Helgerth, Andreas Christmann
Algorithms in machine learning and AI do critically depend on at least three key components: (i) the risk function, which is the expectation of the loss function, (ii) the function…
stat.ML2024
Bootstrap SGD: Algorithmic Stability and Robustness
Andreas Christmann, Yunwen Lei
In this paper some methods to use the empirical bootstrap approach for stochastic gradient descent (SGD) to minimize the empirical risk over a separable Hilbert space are investiga…