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cs.LG2021★ 1 cited
Mixability made efficient: Fast online multiclass logistic regression
Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
Mixability has been shown to be a powerful tool to obtain algorithms with optimal regret. However, the resulting methods often suffer from high computational complexity which has r…
cs.LG2020★ 6 cited
Efficient improper learning for online logistic regression
Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
We consider the setting of online logistic regression and consider the regret with respect to the 2-ball of radius B. It is known (see [Hazan et al., 2014]) that any proper algorit…