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Found 3 papers, 1 papers with code
Mixability made efficient: Fast online multiclass logistic regression
Mixability has been shown to be a powerful tool to obtain algorithms with optimal regret.
Efficient improper learning for online logistic regression
We consider the setting of online logistic regression and consider the regret with respect to the 2-ball of radius B.
Efficient online learning with kernels for adversarial large scale problems
For $d$-dimensional inputs, we provide a (close to) optimal regret of order $O((\log n)^{d+1})$ with per-round time complexity and space complexity $O((\log n)^{2d})$.
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