Sciweavers

13 search results - page 1 / 3
» Combining Labeled and Unlabeled Data for Learning Cross-Docu...
Sort
View
IJCNLP
2004
Springer
13 years 10 months ago
Combining Labeled and Unlabeled Data for Learning Cross-Document Structural Relationships
Multi-document discourse analysis has emerged with the potential of improving various NLP applications. Based on the newly proposed Cross-document Structure Theory (CST), this pap...
Zhu Zhang, Dragomir R. Radev
EMNLP
2007
13 years 6 months ago
Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
Jun Suzuki, Akinori Fujino, Hideki Isozaki
CIKM
2011
Springer
12 years 4 months ago
Semi-supervised multi-task learning of structured prediction models for web information extraction
Extracting information from web pages is an important problem; it has several applications such as providing improved search results and construction of databases to serve user qu...
Paramveer S. Dhillon, Sundararajan Sellamanickam, ...
ICML
2005
IEEE
14 years 5 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
ICCV
2009
IEEE
14 years 8 months ago
Sparsity Induced Similarity Measure for Label Propagation
Graph-based semi-supervised learning has gained considerable interests in the past several years thanks to its effectiveness in combining labeled and unlabeled data through labe...
Hong Cheng, Zicheng Liu, Jie Yang