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Recently, much work has been done on extending the scope of online learning and incremental stochastic optimization algorithms.
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Logarithmic regret algorithms for online convex optimization
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Mind the duality gap: Logarithmic regret algorithms for online optimization
Shai Shalev-Shwartz and Sham M Kakade · 2009
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Dual averaging method for regularized stochastic learning and online optimization
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A generalized online mirror descent with applications to classification and regression
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Global optimality of local search for low rank matrix recovery
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Matrix completion has no spurious local minimum
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