We study task assignment under adverse selection and moral hazard. In the single-task setting, agents privately know their types, which determine their success probabilities and effort costs. Based on the agents'reported types, the principal selects an agent to perform the task and offers a success-contingent payment....
Matteo Bollini, Matteo Castiglioni, A. Marchesi· 0 citations
We study online profit maximization in multilateral trade, a setting that generalizes both dynamic pricing and bilateral trade. At each round, an intermediary posts prices to buyers and offers payments to sellers; trade occurs only if every agent accepts. We consider valuations drawn from an unknown joint distribution,...
Francesco Bacchiocchi, Matteo Castiglioni, Anna Lunghi et al.· 0 citations
An algorithm achieving regret $\widetilde{\mathcal{O}}(T^{7/10})$ is designed, improving over the previous best-known bound of $\widetilde{\mathcal{O}}(T^{3/4})$ and showing that the curse of dimensionality can be at least partially lifted for this class of objectives.
Matteo Castiglioni, Anna Lunghi, A. Marchesi· arXiv.org· 0 citations
We study the simultaneous approximation of constant-degree polynomials over convex sets. For any family of $m$ degree-$d$ polynomials and any convex set ${H} \subseteq \mathbb{R}_{\ge0}^n$, we construct an $\epsilon$-Cover of the joint value set $\{(f_1(x), \dots, f_m(x)) : x \in {H}\}$ in the $\ell_\infty$-norm. This...
Martino Bernasconi, Matteo Castiglioni, Andrea Celli et al.· arXiv.org· 1 citation
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