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ML
2008
ACM
15 years 4 months ago
Margin-based first-order rule learning
Abstract We present a new margin-based approach to first-order rule learning. The approach addresses many of the prominent challenges in first-order rule learning, such as the comp...
Ulrich Rückert, Stefan Kramer
CVIU
2004
115views more  CVIU 2004»
15 years 4 months ago
Dynamic learning from multiple examples for semantic object segmentation and search
We present a novel ``dynamic learning'' approach for an intelligent image database system to automatically improve object segmentation and labeling without user interven...
Yaowu Xu, Eli Saber, A. Murat Tekalp
PAMI
2011
14 years 11 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
PAKDD
2011
ACM
473views Data Mining» more  PAKDD 2011»
14 years 10 months ago
 Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy Hospedales, Shaogang Gong and Tao Xiang
WWW
2001
ACM
16 years 5 months ago
IEPAD: information extraction based on pattern discovery
The research in information extraction (IE) regards the generation of wrappers that can extract particular information from semistructured Web documents. Similar to compiler gener...
Chia-Hui Chang, Shao-Chen Lui