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» Learning with Constrained and Unlabelled Data
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JMLR
2010
127views more  JMLR 2010»
13 years 4 months ago
Cross-associating unlabelled timbre distributions to create expressive musical mappings
In timbre remapping applications such as concatenative synthesis, an audio signal is used as a template, and a mapping process derives control data for some audio synthesis algori...
Dan Stowell, Mark D. Plumbley
TAL
2010
Springer
13 years 8 months ago
The Effect of Semi-supervised Learning on Parsing Long Distance Dependencies in German and Swedish
This paper shows how the best data-driven dependency parsers available today [1] can be improved by learning from unlabeled data. We focus on German and Swedish and show that label...
Anders Søgaard, Christian Rishøj
CVPR
2009
IEEE
15 years 5 months ago
Robust Multi-Class Transductive Learning with Graphs
Graph-based methods form a main category of semisupervised learning, offering flexibility and easy implementation in many applications. However, the performance of these methods...
Wei Liu (Columbia University), Shih-fu Chang (Colu...
TASLP
2010
144views more  TASLP 2010»
13 years 4 months ago
Active Learning With Sampling by Uncertainty and Density for Data Annotations
To solve the knowledge bottleneck problem, active learning has been widely used for its ability to automatically select the most informative unlabeled examples for human annotation...
Jingbo Zhu, Huizhen Wang, Benjamin K. Tsou, Matthe...
CASCON
2001
148views Education» more  CASCON 2001»
13 years 11 months ago
Email classification with co-training
The main problems in text classification are lack of labeled data, as well as the cost of labeling the unlabeled data. We address these problems by exploring co-training - an algo...
Svetlana Kiritchenko, Stan Matwin