We present a new approach to the polymorphic typing of data accepting in-place modification in ML-like languages. This approach is based on restrictions over type generalization,...
Most existing decision tree inducers are very fast due to their greedy approach. In many real-life applications, however, we are willing to allocate more time to get better decisi...
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
As users navigate online social spaces, they encounter numerous personal profiles, each displaying a unique constellation of attributes. How do users make sense of this informatio...
Scientific and statistical inferences build heavily on explicit, parametric models, and often with good reasons. However, the limited scope of parametric models and the increasin...