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IDA
2005
Springer
15 years 10 months ago
Removing Statistical Biases in Unsupervised Sequence Learning
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize the...
Yoav Horman, Gal A. Kaminka
IJCAI
2003
15 years 5 months ago
Inductive Learning in Less Than One Sequential Data Scan
Most recent research of scalable inductive learning on very large dataset, decision tree construction in particular, focuses on eliminating memory constraints and reducing the num...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo
AAAI
2011
14 years 4 months ago
CCRank: Parallel Learning to Rank with Cooperative Coevolution
We propose CCRank, the first parallel algorithm for learning to rank, targeting simultaneous improvement in learning accuracy and efficiency. CCRank is based on cooperative coev...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...
ICSE
2012
IEEE-ACM
13 years 6 months ago
Recovering traceability links between an API and its learning resources
—Large frameworks and libraries require extensive developer learning resources, such as documentation and mailing lists, to be useful. Maintaining these learning resources is cha...
Barthélémy Dagenais, Martin P. Robil...
ICPR
2004
IEEE
16 years 5 months ago
Joint Spatial and Temporal Structure Learning for Task based Control
We present an example of a joint spatial and temporal task learning algorithm that results in a generative model that has applications for on-line visual control. We review work o...
Hilary Buxton, Kingsley Sage