Low-rank approximation of image collections (e.g., via
PCA) is a popular tool in many areas of computer vision.
Yet, surprisingly little is known justifying the observation
that...
Abstract-Failures of Internet services and enterprise systems lead to user dissatisfaction and considerable loss of revenue. Since manual diagnosis is often laborious and slow, the...
This paper examines the problem of real-time estimation of the capacity, which is also known as the bottleneck bandwidth, of a network path using end-to-end measurements in a vide...
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
We examine the problem of evaluating a policy in the contextual bandit setting using only observations collected during the execution of another policy. We show that policy evalua...
John Langford, Alexander L. Strehl, Jennifer Wortm...