Regret vs. Bandwidth Trade-off for Recommendation Systems
classification
💻 cs.IR
cs.LGstat.ML
keywords
bandwidthcaserecommendationregretsystemsbanditbroadcastconsider
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We consider recommendation systems that need to operate under wireless bandwidth constraints, measured as number of broadcast transmissions, and demonstrate a (tight for some instances) tradeoff between regret and bandwidth for two scenarios: the case of multi-armed bandit with context, and the case where there is a latent structure in the message space that we can exploit to reduce the learning phase.
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