Sparse Learning for Large-scale and High-dimensional Data: A Randomized Convex-concave Optimization Approach

12 Nov 2015Lijun ZhangTianbao YangRong JinZhi-Hua Zhou

In this paper, we develop a randomized algorithm and theory for learning a sparse model from large-scale and high-dimensional data, which is usually formulated as an empirical risk minimization problem with a sparsity-inducing regularizer. Under the assumption that there exists a (approximately) sparse solution with high classification accuracy, we argue that the dual solution is also sparse or approximately sparse... (read more)

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