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Suykens, “Hybrid conditional gradient-smoothing algorithms with applications to sparse and low rank regularization
- Regularization, Optimization, Kernels, and Support Vector Machines
, 2014
"... Conditional gradient methods are old and well studied optimization algorithms. Their origin dates at least to the 50’s and the Frank-Wolfe algorithm for quadratic programming [18] but they apply to much more general optimization problems. General formulations of conditional gradient algorithms have ..."
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Conditional gradient methods are old and well studied optimization algorithms. Their origin dates at least to the 50’s and the Frank-Wolfe algorithm for quadratic programming [18] but they apply to much more general optimization problems. General formulations of conditional gradient algorithms have been studied in the
