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stat.ML2019
Quantitative Robustness of Localized Support Vector Machines
Florian Dumpert
The huge amount of available data nowadays is a challenge for kernel-based machine learning algorithms like SVMs with respect to runtime and storage capacities. Local approaches mi…
stat.ML2017★ 1 cited
Universal Consistency and Robustness of Localized Support Vector Machines
Florian Dumpert
The massive amount of available data potentially used to discover patters in machine learning is a challenge for kernel based algorithms with respect to runtime and storage capacit…
stat.ML2016
A short note on extension theorems and their connection to universal consistency in machine learning
Andreas Christmann, Florian Dumpert, Dao-Hong Xiang
Statistical machine learning plays an important role in modern statistics and computer science. One main goal of statistical machine learning is to provide universally consistent a…