activity
20132026
most citedScalable bundling via dense product embeddings

25 citations · 35 across the 15 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

cs.LG2020★ 5 cited

Targeting for long-term outcomes

Jeremy Yang, Dean Eckles, Paramveer Dhillon +1

Decision makers often want to target interventions so as to maximize an outcome that is observed only in the long-term. This typically requires delaying decisions until the outcome…

stat.ME2020

Reducing Interference Bias in Online Marketplace Pricing Experiments

David Holtz, Ruben Lobel, Inessa Liskovich +1

Online marketplace designers frequently run A/B tests to measure the impact of proposed product changes. However, given that marketplaces are inherently connected, total average tr…

stat.AP2020

Limiting Bias from Test-Control Interference in Online Marketplace Experiments

David Holtz, Sinan Aral

In an A/B test, the typical objective is to measure the total average treatment effect (TATE), which measures the difference between the average outcome if all users were treated a…

cs.SI2020

The Engagement-Diversity Connection: Evidence from a Field Experiment on Spotify

David Holtz, Benjamin Carterette, Praveen Chandar +3

It remains unknown whether personalized recommendations increase or decrease the diversity of content people consume. We present results from a randomized field experiment on Spoti…

cs.LG2020★ 25 cited

Scalable bundling via dense product embeddings

Madhav Kumar, Dean Eckles, Sinan Aral

Bundling, the practice of jointly selling two or more products at a discount, is a widely used strategy in industry and a well examined concept in academia. Historically, the focus…