Our goal is to fit the multiple instances (or structures) of a generic model existing in data. Here we propose a novel model selection scheme to estimate the number of genuine str...
Many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from...
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Hierarchies are an intuitive and effective organization paradigm for data. Of late there has been considerable research on automatically learning hierarchical organizations of dat...