The recent explosion of on-line information in Digital Libraries and on the World Wide Web has given rise to a number of query-based search engines and manually constructed topica...
Mehran Sahami, Salim Yusufali, Michelle Q. Wang Ba...
: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
The problem of model selection is considerably important for acquiring higher levels of generalization capability in supervised learning. In this paper, we propose a new criterion ...
Memory latency is an important bottleneck in system performance that cannot be adequately solved by hardware alone. Several promising software techniques have been shown to addres...
Mark Horowitz, Margaret Martonosi, Todd C. Mowry, ...
In this paper, we propose a Bayesian learning approach to promoting diversity for information retrieval in biomedicine and a re-ranking model to improve retrieval performance in t...