assortment-optimization

This paper proposes a framework for Markov chain choice models with panel data, including estimation via novel EM algorithms that leverage partial-ordering preference information, personalized choice prediction, and assortment optimization. Experimental results on synthetic data and the sushi dataset show improvements over traditional methods.