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We demonstrate how to scalably solve a class of constrained self-concordant minimization problems using linear minimization oracles (LMO) over the constraint set.
An algorithm for quadratic programming
M. Frank and P. Wolfe · 1956
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Frank-Wolfe works for non-lipschitz continuous gradient objectives: Scalable poisson phase retrieval
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Finite-sample Analysis of M-estimators using Self-concordance
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Faster rates for the frank-wolfe method over strongly-convex sets
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On the global linear convergence of Frank-Wolfe optimization variants
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Generalized Self-Concordant Functions: A Recipe for Newton-Type Methods
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A new homotopy proximal variable-metric framework for composite convex minimization
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