267 citations · 813 across the 34 of their papers we have counts for
4 papers · 1 filter
Which Minimizer Does My Neural Network Converge To?
Manuel Nonnenmacher, David Reeb, Ingo Steinwart
The loss surface of an overparameterized neural network (NN) possesses many global minima of zero training error. We explain how common variants of the standard NN training procedu…
Reproducing Kernel Hilbert Spaces Cannot Contain all Continuous Functions on a Compact Metric Space
Ingo Steinwart
Given an uncountable, compact metric space, we show that there exists no reproducing kernel Hilbert space that contains the space of all continuous functions on this compact space.
Adaptive Learning Rates for Support Vector Machines Working on Data with Low Intrinsic Dimension
Thomas Hamm, Ingo Steinwart
We derive improved regression and classification rates for support vector machines using Gaussian kernels under the assumption that the data has some low-dimensional intrinsic stru…
Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent
David Holzmüller, Ingo Steinwart
We prove that two-layer (Leaky)ReLU networks initialized by e.g. the widely used method proposed by He et al. (2015) and trained using gradient descent on a least-squares loss are…