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Articles by Ingo Steinwart

Better by Default: Strong Pre-Tuned MLPs and Boosted Trees on Tabular Data
6 days ago by David Holzmüller and others
Machine Learning
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension
6 November 2024 by Moritz Haas and others
Machine Learning, Statistics Theory
Conditioning of Banach Space Valued Gaussian Random Variables: An Approximation Approach Based on Martingales
6 August 2024 by Ingo Steinwart
Probability, Machine Learning
When does a Gaussian process have its paths in a reproducing kernel Hilbert space?
16 July 2024 by Ingo Steinwart
Probability
Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers
28 April 2024 by Marvin Pförtner and others
Machine Learning, Numerical Analysis
Which Spaces can be Embedded in Reproducing Kernel Hilbert Spaces?
20 February 2024 by Max Schölpple and Ingo Steinwart at LogoUniversity of Stuttgart
Functional Analysis, Statistics Theory
A Framework and Benchmark for Deep Batch Active Learning for Regression
18 August 2022 by David Holzmüller and others
Machine Learning, Neural and Evolutionary Computing
Which Minimizer Does My Neural Network Converge To?
30 June 2022 by Manuel Nonnenmacher and others
Machine Learning
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning
30 June 2022 by Manuel Nonnenmacher and others
Machine Learning, Computer Vision and Pattern Recognition
Utilizing Expert Features for Contrastive Learning of Time-Series Representations
23 June 2022 by Manuel Nonnenmacher and others
Machine Learning, Artificial Intelligence
Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments
20 September 2021 by Viktor Zaverkin and others
Computational Physics, Machine Learning
Empirical Risk Minimization in the Interpolating Regime with Application to Neural Network Learning
23 July 2021 by Nicole Mücke and Ingo Steinwart
Machine Learning
Intrinsic Dimension Adaptive Partitioning for Kernel Methods
16 July 2021 by Thomas Hamm and Ingo Steinwart
Statistics Theory
Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent
31 July 2020 by David Holzmüller and Ingo Steinwart
Machine Learning
A Closer Look at Covering Number Bounds for Gaussian Kernels
22 July 2020 by Ingo Steinwart and Simon Fischer
Functional Analysis
Adaptive Learning Rates for Support Vector Machines Working on Data with Low Intrinsic Dimension
17 March 2020 by Thomas Hamm and Ingo Steinwart
Statistics Theory
Reproducing Kernel Hilbert Spaces Cannot Contain all Continuous Functions on a Compact Metric Space
13 March 2020 by Ingo Steinwart
Functional Analysis, Machine Learning
Improved Classification Rates for Localized SVMs
26 September 2019 by Ingrid Blaschzyk and Ingo Steinwart
Statistics Theory
PAC-Bayesian Bounds for Deep Gaussian Processes
22 September 2019 by Roman Föll and Ingo Steinwart
Statistics Theory
A Sober Look at Neural Network Initializations
4 September 2019 by Ingo Steinwart
Machine Learning
Adaptive Clustering Using Kernel Density Estimators
17 August 2019 by Ingo Steinwart and others
Machine Learning, Methodology
Best-scored Random Forest Classification
27 May 2019 by Hanyuan Hang and others
Machine Learning
Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm
22 May 2019 by Simon Fischer and Ingo Steinwart
Machine Learning
Optimal Learning with Anisotropic Gaussian SVMs
4 October 2018 by Hanyuan Hang and Ingo Steinwart
Machine Learning
Spatial Decompositions for Large Scale SVMs
8 February 2018 by Philipp Thomann and others
Machine Learning
Strictly proper kernel scores and characteristic kernels on compact spaces
14 December 2017 by Ingo Steinwart and Johanna Ziegel
Functional Analysis, Statistics Theory
Learning Rates for Kernel-Based Expectile Regression
27 February 2017 by Muhammad Farooq and Ingo Steinwart
Machine Learning
liquidSVM: A Fast and Versatile SVM package
22 February 2017 by Ingo Steinwart and Philipp Thomann
Machine Learning
Improved Classification Rates under Refined Margin Conditions
17 February 2017 by Ingrid Blaschzyk and Ingo Steinwart
Statistics Theory
Learning with Hierarchical Gaussian Kernels
2 December 2016 by Ingo Steinwart and others
Machine Learning
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