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Feb, 2012
关于预测稀疏编码的样本复杂度
On the Sample Complexity of Predictive Sparse Coding
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Nishant A. Mehta, Alexander G. Gray
TL;DR
本文研究预测性稀疏编码的推广性能,提出了学习界限并通过稳定性特征刻画了稀疏编码器的性质,进而在超完备和高维情况下提供了精确的估计.
Abstract
predictive sparse coding
algorithms recently have demonstrated impressive performance on a variety of supervised tasks, but they lack a learning theoretic analysis. We establish the first generalization bounds for
predi
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