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EMNLP
2009
13 years 5 months ago
Active Learning by Labeling Features
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Gregory Druck, Burr Settles, Andrew McCallum
PRL
2006
117views more  PRL 2006»
13 years 7 months ago
Motion features to enhance scene segmentation in active visual attention
A new computational model for active visual attention is introduced in this paper. The method extracts motion and shape features from video image sequences, and integrates these f...
María T. López, Antonio Ferná...
IMSCCS
2007
IEEE
14 years 2 months ago
Asymmetric Bagging and Feature Selection for Activities Prediction of Drug Molecules
Background: Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cy...
Guo-Zheng Li, Hao-Hua Meng, Mary Qu Yang, Jack Y. ...
KDD
2007
ACM
202views Data Mining» more  KDD 2007»
14 years 8 months ago
Support feature machine for classification of abnormal brain activity
In this study, a novel multidimensional time series classification technique, namely support feature machine (SFM), is proposed. SFM is inspired by the optimization model of suppo...
Wanpracha Art Chaovalitwongse, Ya-Ju Fan, Rajesh C...
CVPR
2007
IEEE
14 years 9 months ago
Unsupervised Activity Perception by Hierarchical Bayesian Models
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
Xiaogang Wang, Xiaoxu Ma, Eric Grimson