There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
Personalization actions that tailor the Web experience to a particular user are an integral component of recommender systems. Here, product knowledge - either hand-coded or “mine...
Query result clustering has recently attracted a lot of attention to provide users with a succinct overview of relevant results. However, little work has been done on organizing t...
Jongwuk Lee, Seung-won Hwang, Zaiqing Nie, Ji-Rong...