Transfer bounds for linear feature learning

DOI10.1007/s10994-009-5109-7zbMath1470.68146OpenAlexW1978164656MaRDI QIDQ1959489

Andreas Maurer

Publication date: 7 October 2010

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-009-5109-7

zbMATH Keywords

kernel methodstransfer learninglearning to learn

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (10)

A chain rule for the expected suprema of Gaussian processes ⋮ Slepian's inequality for Gaussian processes with respect to weak majorization ⋮ Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach ⋮ Inequalities for Gaussian random variables under Archimedean copula dependence ⋮ Slepian's inequality with respect to majorization ⋮ Unnamed Item ⋮ A note on Slepian's inequality based on majorization ⋮ A Vector-Contraction Inequality for Rademacher Complexities ⋮ Multi-task and Lifelong Learning of Kernels ⋮ Risk bound of transfer learning using parametric feature mapping and its application to sparse coding

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• 10.1162/153244303321897690
• Neural Network Learning
• Learning Theory and Kernel Machines

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