Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
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 ...
In order to support work-integrated learning scenarios task- and competency-aware knowledge services are needed. In this paper we introduce three key knowledge services of the APOS...
Stefanie N. Lindstaedt, Peter Scheir, Robert Lokai...
Microblogs have become an important source of information for the purpose of marketing, intelligence, and reputation management. Streams of microblogs are of great value because o...
Eye tracking experiments have shown that titles of Web search results play a crucial role in guiding a user’s search process. We present a machine-learned algorithm that trains ...
Tapas Kanungo, Nadia Ghamrawi, Ki Yuen Kim, Lawren...