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ACL
2008
14 years 11 months ago
Analyzing the Errors of Unsupervised Learning
We identify four types of errors that unsupervised induction systems make and study each one in turn. Our contributions include (1) using a meta-model to analyze the incorrect bia...
Percy Liang, Dan Klein
IEEECIT
2010
IEEE
14 years 8 months ago
A Learning Spectrum Hole Prediction Model for Cognitive Radio Systems
—In this paper, we present a new spectrum-hole prediction model for cognitive radio (CR) systems based on the IEEE 802.11 wireless local areas networks. We have also analyzed the...
Zhigang Wen, Chunxiao Fan, Xiaoying Zhang, Yuexin ...
CVPR
2007
IEEE
15 years 12 months ago
Adaptive Distance Metric Learning for Clustering
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
Jieping Ye, Zheng Zhao, Huan Liu
ICANN
2010
Springer
14 years 11 months ago
Unsupervised Learning of Relations
Learning processes allow the central nervous system to learn relationships between stimuli. Even stimuli from different modalities can easily be associated, and these associations ...
Matthew Cook, Florian Jug, Christoph Krautz, Angel...
AIED
2011
Springer
14 years 1 months ago
Learning by Teaching SimStudent - An Initial Classroom Baseline Study Comparing with Cognitive Tutor
: This paper describes an application of a machine-learning agent, SimStudent, as a teachable peer learner that allows a student to learn by teaching. SimStudent has been integrate...
Noboru Matsuda, Evelyn Yarzebinski, Victoria Keise...