Research map / Bandits and online learning / Contextual bandits and Thompson sampling
Multiple-Play Bandits in the Position-Based Model
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use PBM-PIE instead of RBA-KL-UCB | Search advertising simulations with parameters estimated from real data · KDD Cup 2012 track 2-derived query models | regret | Helped |
| Use PBM-TS instead of RBA-KL-UCB | Search advertising simulations with parameters estimated from real data · KDD Cup 2012 track 2-derived query models | regret | Helped |
| Use RBA-KL-UCB instead of PBM-UCB | Search advertising simulations with parameters estimated from real data · KDD Cup 2012 track 2-derived query models | regret | Helped |
| Use PBM-PIE instead of RBA-KL-UCB | Multiple-play PBM simulation · Synthetic PBM simulation | regret | Mixed |
| Use PBM-TS instead of RBA-KL-UCB | Multiple-play PBM simulation · Synthetic PBM simulation | regret | Mixed |
| Approximate the censored-feedback posterior with a Beta distribution rather than sampling from the exact posterior | PBM-TS · PBM with parameter values close to one | exploration | Hurt |
| Fix exploration at the last position rather than adapting the exploration position to the data | PBM-PIE · PBM when the optimal exploration position is not L | regret | Hurt |
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