In this paper, we study learning-augmented algorithms for the Bahncard problem.

's matching capacity will be reduced

We study the task of learning SIMs in the agnostic (a.k.a.

In the last few years, the ability to effectively summarize data has gained importance due to the advent of massive datasets in many fields.

We analyze how lookback improves, or not, the competitive ratio in prophet inequalities in different order models.

A recent trend in online algorithms has seen the use of future predictions generated by ML techniques to bypass pessimistic worst-case lower bounds.

In classic auction theory, reserve prices are known to be effective for improving revenue for the auctioneer against quasi-linear utility maximizing bidders.

In the last few years, the ability to effectively summarize data has gained importance due to the advent of massive datasets in many fields.

An important goal of modern scheduling systems is to efficiently manage power usage.