In the strategic facility location problem, a set of agents report their locations in a metric
space and the goal is to use these reports to open a new facility, minimizing an aggregate …

We consider the fundamental problem of designing a truthful single-item auction with the
challenging objective of extracting a large fraction of the highest agent valuation as revenue …

Aiming to overcome some of the limitations of worst-case analysis, the recently proposed
framework of" algorithms with predictions" allows algorithms to be augmented with a …

In the metric distortion problem there is a set of candidates and a set of voters, all residing in
the same metric space. The objective is to choose a candidate with minimum social cost …

The competitive auction was first proposed by Goldberg, Hartline, and Wright. In their paper,
they introduce the competitive analysis framework of online algorithm designing into the …

We provide the first analysis of (deferred acceptance) clock auctions in the learning-
augmented framework. These auctions satisfy a unique list of very appealing properties …

An important challenge in robust machine learning is when training data is provided by
strategic sources who may intentionally report erroneous data for their own benefit. A line of …

The realm of algorithms with predictions has led to the development of several new
algorithms that leverage (potentially erroneous) predictions to enhance their performance …

Our work revisits the design of mechanisms via the learning-augmented framework. In this
model, the algorithm is enhanced with imperfect (machine-learned) information concerning …

Modern-day human-scale marketplaces such as recommender systems, advertisement
markets, matching platforms, supply chain industries, electronic commerce platforms, and …