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cs.LG2023
An Improved Uniform Convergence Bound with Fat-Shattering Dimension
Roberto Colomboni, Emmanuel Esposito, Andrea Paudice
The fat-shattering dimension characterizes the uniform convergence property of real-valued functions. The state-of-the-art upper bounds feature a multiplicative squared logarithmic…
cs.LG2023
Delayed Bandits: When Do Intermediate Observations Help?
Emmanuel Esposito, Saeed Masoudian, Hao Qiu +3
We study a -armed bandit with delayed feedback and intermediate observations. We consider a model where intermediate observations have a form of a finite state, which is observe…
cs.LG2023
On the Minimax Regret for Online Learning with Feedback Graphs
Khaled Eldowa, Emmanuel Esposito, Tommaso Cesari +1
In this work, we improve on the upper and lower bounds for the regret of online learning with strongly observable undirected feedback graphs. The best known upper bound for this pr…