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In this episode, we explore how Lyft tackles interference bias in marketplace experiments using Marketplace Marginal Values (MMVs). We break down why interference is a natural challenge in two-sided platforms like Lyft, and how their team uses optimization, simulation, and advanced metrics to measure causal effects more reliably.
For more details, check out the original tech blog linked here: https://eng.lyft.com/using-marketplace-marginal-values-to-address-interference-bias-a11aff6e670f
By Pan Wu5
99 ratings
In this episode, we explore how Lyft tackles interference bias in marketplace experiments using Marketplace Marginal Values (MMVs). We break down why interference is a natural challenge in two-sided platforms like Lyft, and how their team uses optimization, simulation, and advanced metrics to measure causal effects more reliably.
For more details, check out the original tech blog linked here: https://eng.lyft.com/using-marketplace-marginal-values-to-address-interference-bias-a11aff6e670f

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