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Rémi Jézéquel

2 accepted papers

2021

Mixability made efficient: Fast online multiclass logistic regression

NeurIPS 2021spotlight

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 reduced their practical applicability. For example, in the case of multiclass logistic regression, the aggregating foreca…

Cited by 13SourcePDFScholar
2019

Efficient online learning with kernels for adversarial large scale problems

NeurIPS 2019poster

We are interested in a framework of online learning with kernels for low-dimensional, but large-scale and potentially adversarial datasets. We study the computational and theoretical performance of online variations of kernel Ridge regression. Despite its simplicity, the algorithm we study is the f…