13 citations · 50 across the 10 of their papers we have counts for
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cs.AI2020★ 3 cited
Loss Bounds for Approximate Influence-Based Abstraction
Elena Congeduti, Alexander Mey, Frans A. Oliehoek
Sequential decision making techniques hold great promise to improve the performance of many real-world systems, but computational complexity hampers their principled application. I…
cs.LG2020★ 1 cited
A Note on High-Probability versus In-Expectation Guarantees of Generalization Bounds in Machine Learning
Alexander Mey
Statistical machine learning theory often tries to give generalization guarantees of machine learning models. Those models naturally underlie some fluctuation, as they are based on…
cs.LG2020★ 1 cited
A Brief Prehistory of Double Descent
Marco Loog, Tom Viering, Alexander Mey +2
In their thought-provoking paper [1], Belkin et al. illustrate and discuss the shape of risk curves in the context of modern high-complexity learners. Given a fixed training sample…