Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...
Our KNOWITALL system aims to automate the tedious process of extracting large collections of facts (e.g., names of scientists or politicians) from the Web in an autonomous, domain...
Oren Etzioni, Michael J. Cafarella, Doug Downey, A...
We present a probabilistic method for path planning that considers trajectories constrained by both the environment and an ensemble of restrictions or preferences on preferred mot...
In text categorization, term weighting methods assign appropriate weights to the terms to improve the classification performance. In this study, we propose an effective term weigh...
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...