We formalize the associative bandit problem framework introduced by Kaelbling as a learning-theory problem. The learning environment is modeled as a k-armed bandit where arm payof...
Alexander L. Strehl, Chris Mesterharm, Michael L. ...
How to assign appropriate weights to terms is one of the critical issues in information retrieval. Many term weighting schemes are unsupervised. They are either based on the empir...
We propose a method for recursive segmentation of the left ventricle (LV) across a temporal sequence of magnetic resonance (MR) images. The approach involves a technique for learn...
To understand how and why individuals make use of emerging information assimilation services on the Web as part of their daily routine, we combined video recordings of online acti...
It has been observed that even highly optimized software programs perform "redundant" computations during their execution, due to the nature (statistics) of the values a...