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Skill Disentanglement in Reproducing Kernel Hilbert Space
Proceedings of the AAAI Conference on Artificial IntelligenceUnsupervised Skill Discovery aims at learning diverse skills without any extrinsic rewards and leverage them as prior for learning a variety of downstream tasks. Existing approaches to unsupervised reinforcement learning typically involve discovering skills through empowerment-driven techniques or by maximizing entropy to encourage exploration. However,
Vedant Dave, Elmar Rueckert
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Subspace classifier in reproducing kernel Hilbert space
IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 2003To improve the performance of subspace classifier, it is effective to reduce the dimensionality of the intersections between subspaces. For this purpose, the feature space is mapped implicitly to a high dimensional reproducing kernel Hilbert space and the subspace classifier is applied in this space.
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Reproducing kernel Hilbert spaces in probability and statistics
, 2004A. Berlinet, C. Thomas-Agnan
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An Introduction to the Theory of Reproducing Kernel Hilbert Spaces
, 2016V. Paulsen, M. Raghupathi
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Reproducing Kernels of Hilbert Spaces
2025 27th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)Diane Guignard, Olivier D. Lafitte
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Kernels and Reproducing Kernel Hilbert Spaces
2008Ingo Steinwart, Andreas Christmann
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