However, categorical features present a unique challenge as they require embedding a typically vast vocabulary into a smaller vector space for further calculations.
Interactive decision making, encompassing bandits, contextual bandits, and reinforcement learning, has recently been of interest to theoretical studies of experimentation design and recommender system algorithm research.