46 citations · 58 across the 5 of their papers we have counts for
3 papers · 1 filter
ConjointNet: Enhancing Conjoint Analysis for Preference Prediction with Representation Learning
Yanxia Zhang, Francine Chen, Shabnam Hakimi +9
Understanding consumer preferences is essential to product design and predicting market response to these new products. Choice-based conjoint analysis is widely used to model user…
Machine learning reveals how personalized climate communication can both succeed and backfire
Totte Harinen, Alexandre Filipowicz, Shabnam Hakimi +3
Different advertising messages work for different people. Machine learning can be an effective way to personalise climate communications. In this paper we use machine learning to r…
Feature Selection Methods for Uplift Modeling and Heterogeneous Treatment Effect
Zhenyu Zhao, Yumin Zhang, Totte Harinen +1
Uplift modeling is a causal learning technique that estimates subgroup-level treatment effects. It is commonly used in industry and elsewhere for tasks such as targeting ads. In a…