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ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
16 years 1 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
CIKM
2009
Springer
16 years 1 months ago
Scalable learning of collective behavior based on sparse social dimensions
The study of collective behavior is to understand how individuals behave in a social network environment. Oceans of data generated by social media like Facebook, Twitter, Flickr a...
Lei Tang, Huan Liu
AIME
1997
Springer
15 years 10 months ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
COLT
1997
Springer
15 years 10 months ago
On-line Learning and the Metrical Task System Problem
We relate two problems that have been explored in two distinct communities. The first is the problem of combining expert advice, studied extensively in the computational learning...
Avrim Blum, Carl Burch
KDD
2012
ACM
207views Data Mining» more  KDD 2012»
13 years 9 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang