Mikael Moller Hogsgaard — accepted AI-conference papers

2026

The Interplay Between Interpolation and Aggregation in Regression: Optimal Sample Complexity

Mikael Moller Hogsgaard, Kasper Green Larsen, Liang-Yu Zou

ICML 2026poster

This work investigates theoretically the interplay between interpolation and aggregation in regression. We establish that the $\gamma$-graph dimension characterizes learnability for a broad class of natural aggregation procedures. Furthermore, we prove that an extremely simple aggregation procedure,…

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2026

The Optimal Sample Complexity of Linear Contracts

Mikael Moller Hogsgaard

ICML 2026poster

In this paper, we settle the problem of learning optimal linear contracts from data in the offline setting, where agent types are drawn from an unknown distribution and the principal's goal is to design a contract that maximizes her expected utility. Specifically, our analysis shows that the simple …

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