Conditional gradient methods via stochastic path-integrated differential estimator
We propose a class of novel variance-reduced stochastic conditional gradient methods. By adopting the recent stochastic path-integrated differential estimator technique (SPIDER) of Fang ct al. (2018) for the classical Frank-Wolfe (FW) method, we introduce SPIDER-FW for finite-sum minimization as wel...
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| Format: | Article |
| Language: | English |
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International Machine Learning Society
2021
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| Online Access: | https://hdl.handle.net/1721.1/130530 |