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Nicolò Cesa-Bianchi
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We study the power of cooperation in a network of communicating agents that solve a learning task. Agents use an underlying communication network to get information about what the other agents know. In the talk, we show the extent to which cooperation allows to prove performance bounds that are strictly better than the known bounds for non-cooperating agents. Our results are formulated within the online learning setting, under both the full and partial feedback models.
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