Efficient Gradient Support Pursuit With Less Hard Thresholding for Cardinality-Constrained Learning.
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DOI: 10.1109/tnnls.2021.3087805
Abstract: Recently, stochastic hard thresholding (HT) optimization methods [e.g., stochastic variance reduced gradient hard thresholding (SVRGHT)] are becoming more attractive for solving large-scale sparsity/rank-constrained problems. However, they have much higher HT oracle complexities, especially for high-dimensional… read more here.
Keywords: gradient support; hard thresholding; support pursuit; stochastic variance ... See more keywords