Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
In Proc. of IEEE Conf. on CVPR'2000, Vol.I, pp.222-227, Hilton Head Island, SC, 2000 In many vision applications, the practice of supervised learning faces several difficulti...
Data collection for both training and testing a classifier is a tedious but essential step towards face detection and recognition. It is a piece of cake to collect more than hundre...
In this paper, we present a semi-supervised learning method for web page classification, leveraging click logs to augment training data by propagating class labels to unlabeled si...
Soo-Min Kim, Patrick Pantel, Lei Duan, Scott Gaffn...
Long queries frequently contain many extraneous terms that hinder retrieval of relevant documents. We present techniques to reduce long queries to more effective shorter ones tha...