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PAMI
2011
12 years 10 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
EMNLP
2009
13 years 1 months ago
Semi-Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy
This paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation class...
Longhua Qian, Guodong Zhou, Fang Kong, Qiaoming Zh...
AAAI
2007
13 years 6 months ago
Semi-Supervised Learning by Mixed Label Propagation
Recent studies have shown that graph-based approaches are effective for semi-supervised learning. The key idea behind many graph-based approaches is to enforce the consistency bet...
Wei Tong, Rong Jin
SDM
2011
SIAM
269views Data Mining» more  SDM 2011»
12 years 6 months ago
Semi-Supervised Convolution Graph Kernels for Relation Extraction
Extracting semantic relations between entities is an important step towards automatic text understanding. In this paper, we propose a novel Semi-supervised Convolution Graph Kerne...
Xia Ning, Yanjun Qi
SDM
2004
SIAM
225views Data Mining» more  SDM 2004»
13 years 5 months ago
Active Semi-Supervision for Pairwise Constrained Clustering
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
Sugato Basu, Arindam Banerjee, Raymond J. Mooney