Beyond Globally Optimal: Focused Learning for Improved Recommendations
WWW, pp. 203-212, 2017.
When building a recommender system, how can we ensure that all items are modeled well? Classically, recommender systems are built, optimized, and tuned to improve a global prediction objective, such as root mean squared error. However, as we demonstrate, these recommender systems often leave many items badly-modeled and thus under-served....More
Full Text (Upload PDF)