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ErrorCompensatedX: error compensation for variance reduced algorithms
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Communication cost is one major bottleneck for the scalability for distributed learning.
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Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning Anthony Tompkins 1, Rafael Oliveira 1, 2, Fabio Ramos 1,3 1 School of Computer Science, the University of Sydney, Australia 2
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Simpler phenomena that do not exhibit such variation may be called stationary . The typical kernel based learner canonically relies on a stationary kernel function, a measure of "similarity", to define the prior beliefs over the function space.
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