Sciweavers

ACL
2006
13 years 5 months ago
Relation Extraction Using Label Propagation Based Semi-Supervised Learning
Shortage of manually labeled data is an obstacle to supervised relation extraction methods. In this paper we investigate a graph based semi-supervised learning algorithm, a label ...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...
ACL
2008
13 years 5 months ago
Semi-Supervised Convex Training for Dependency Parsing
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
Qin Iris Wang, Dale Schuurmans, Dekang Lin
PAKDD
2005
ACM
132views Data Mining» more  PAKDD 2005»
13 years 9 months ago
SETRED: Self-training with Editing
Self-training is a semi-supervised learning algorithm in which a learner keeps on labeling unlabeled examples and retraining itself on an enlarged labeled training set. Since the s...
Ming Li, Zhi-Hua Zhou
ACCV
2007
Springer
13 years 10 months ago
MAPACo-Training: A Novel Online Learning Algorithm of Behavior Models
The traditional co-training algorithm, which needs a great number of unlabeled examples in advance and then trains classifiers by iterative learning approach, is not suitable for ...
Heping Li, Zhanyi Hu, Yihong Wu, Fuchao Wu
ICPR
2008
IEEE
13 years 10 months ago
Semi-supervised discriminant analysis based on UDP regularization
We propose a semi-supervised learning algorithm for discriminant analysis, which uses the geometric structure of both labeled and unlabeled samples and perform a manifold regulari...
Huining Qiu, Jian-Huang Lai, Jian Huang, Yu Chen
ICPR
2008
IEEE
13 years 10 months ago
An improvement on learning with local and global consistency
A modified version for semi-supervised learning algorithm with local and global consistency was proposed in this paper. The new method adds the label information, and adopts the g...
Jie Gui, De-Shuang Huang, Zhuhong You
ADMA
2009
Springer
246views Data Mining» more  ADMA 2009»
13 years 11 months ago
Semi Supervised Image Spam Hunter: A Regularized Discriminant EM Approach
Image spam is a new trend in the family of email spams. The new image spams employ a variety of image processing technologies to create random noises. In this paper, we propose a s...
Yan Gao, Ming Yang, Alok N. Choudhary
ICASSP
2009
IEEE
13 years 11 months ago
Using collective information in semi-supervised learning for speech recognition
Training accurate acoustic models typically requires a large amount of transcribed data, which can be expensive to obtain. In this paper, we describe a novel semi-supervised learn...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 4 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy