17 citations · 18 across the 2 of their papers we have counts for
2 papers
cs.IR2022★ 1 cited
Long-run User Value Optimization in Recommender Systems through Content Creation Modeling
Akos Lada, Xiaoxuan Liu, Jens Rischbieth +2
Content recommender systems are generally adept at maximizing immediate user satisfaction but to optimize for the \textit{long-run} user value, we need more statistically sophistic…
cs.AI2016★ 17 cited
Combining observational and experimental data to find heterogeneous treatment effects
Alexander Peysakhovich, Akos Lada
Every design choice will have different effects on different units. However traditional A/B tests are often underpowered to identify these heterogeneous effects. This is especially…