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• W2948846193 abstract "We propose a variant of the Frank-Wolfe algorithm for solving a class of sparse/low-rank optimization problems. Our formulation includes Elastic Net, regularized SVMs and phase retrieval as special cases. The proposed Primal-Dual Block Frank-Wolfe algorithm reduces the per-iteration cost while maintaining linear convergence rate. The per iteration cost of our method depends on the structural complexity of the solution (i.e. sparsity/low-rank) instead of the ambient dimension. We empirically show that our algorithm outperforms the state-of-the-art methods on (multi-class) classification tasks." @default.
• W2948846193 created "2019-06-14" @default.
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• W2948846193 date "2019-06-06" @default.
• W2948846193 modified "2023-09-27" @default.
• W2948846193 title "Primal-Dual Block Frank-Wolfe" @default.
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• W2948846193 hasPublicationYear "2019" @default.
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