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@@ -61,6 +61,8 @@ learning on aggregated data: our learnings are available [here](https://arxiv.or
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  ## Dataset Description
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  This dataset represents a 100M anonymised sample of 30 days of Criteo
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  live data retrieved from third-party cookie traffic on Chrome. Each line corresponds to one impression (a banner)
@@ -107,12 +109,10 @@ display and user-level privacy.
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  for the same user.
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  CriteoPrivateAd is split into 30 parquets (one per day from 1 to 30) in day_int={i} directory.
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- The displays-per-user histograms can be deduced from event_per_user_contribution.csv,< it is useful to build importance sampling ratios and user-level DP.
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- Please, see the companion paper for more details.
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- A precise description of the dataset and each column is available in [the
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- companion paper](https://arxiv.org/abs/2502.12103)
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  ## Dataset Description
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+ A precise description of the dataset and each column is available in [the
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+ companion paper](https://arxiv.org/abs/2502.12103)
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  This dataset represents a 100M anonymised sample of 30 days of Criteo
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  live data retrieved from third-party cookie traffic on Chrome. Each line corresponds to one impression (a banner)
 
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  for the same user.
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  CriteoPrivateAd is split into 30 parquets (one per day from 1 to 30) in day_int={i} directory.
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+ The displays-per-user histograms can be deduced from event_per_user_contribution.csv. It is useful to build importance sampling ratios and user-level DP, as it is detailed in the companion paper.
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+
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