16 citations · 23 across the 7 of their papers we have counts for
7 papers
Stochastic Online Instrumental Variable Regression: Regrets for Endogeneity and Bandit Feedback
Riccardo Della Vecchia, Debabrota Basu
Endogeneity, i.e. the dependence of noise and covariates, is a common phenomenon in real data due to omitted variables, strategic behaviours, measurement errors etc. In contrast, t…
Entropy Regularized Reinforcement Learning with Cascading Networks
Riccardo Della Vecchia, Alena Shilova, Philippe Preux +1
Deep Reinforcement Learning (Deep RL) has had incredible achievements on high dimensional problems, yet its learning process remains unstable even on the simplest tasks. Deep RL us…
Cooperative Online Learning with Feedback Graphs
Nicolò Cesa-Bianchi, Tommaso R. Cesari, Riccardo Della Vecchia
We study the interplay between communication and feedback in a cooperative online learning setting, where a network of communicating agents learn a common sequential decision-makin…
Finding Stable Matchings in PhD Markets with Consistent Preferences and Cooperative Partners
Maximilian Mordig, Riccardo Della Vecchia, Nicolò Cesa-Bianchi +1
We introduce a new algorithm for finding stable matchings in multi-sided matching markets. Our setting is motivated by a PhD market of students, advisors, and co-advisors, and can…
Two-Sided Matching Markets in the ELLIS 2020 PhD Program
Maximilian Mordig, Riccardo Della Vecchia, Nicolò Cesa-Bianchi +1
The ELLIS PhD program is a European initiative that supports excellent young researchers by connecting them to leading researchers in AI. In particular, PhD students are supervised…
An Efficient Algorithm for Cooperative Semi-Bandits
Riccardo Della Vecchia, Tommaso Cesari
We consider the problem of asynchronous online combinatorial optimization on a network of communicating agents. At each time step, some of the agents are stochastically activated,…