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PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
13 years 7 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud
SDM
2010
SIAM
259views Data Mining» more  SDM 2010»
13 years 11 months ago
Semi-supervised Bio-named Entity Recognition with Word-Codebook Learning
We describe a novel semi-supervised method called WordCodebook Learning (WCL), and apply it to the task of bionamed entity recognition (bioNER). Typical bioNER systems can be seen...
Pavel P. Kuksa, Yanjun Qi
IDA
2007
Springer
13 years 10 months ago
Removing biases in unsupervised learning of sequential patterns
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Yoav Horman, Gal A. Kaminka
ECCV
2008
Springer
14 years 12 months ago
Output Regularized Metric Learning with Side Information
Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application ...
Wei Liu, Steven C. H. Hoi, Jianzhuang Liu
SDM
2012
SIAM
261views Data Mining» more  SDM 2012»
12 years 10 days ago
Combining Active Learning and Dynamic Dimensionality Reduction
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
Mustafa Bilgic