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» Learning from Multiple Annotators with Gaussian Processes
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IDA
2010
Springer
14 years 10 months ago
Multi-dimensional data construction method with its application to learning from small-sample-sets
Insufficient training data is one of the major problems in neural network learning, because it leads to poor learning performance. In order to enhance an intelligent learning proc...
Hsiao-Fan Wang, Chun-Jung Huang
ICPR
2010
IEEE
15 years 6 months ago
Automatic Pathology Annotation on Medical Images: A Statistical Machine Translation Framework
Large number of medical images are produced daily in hospitals and medical institutions, the needs to efficiently process, index, search and retrieve these images are great. In t...
Tianxia Gong, Shimiao Li, Chew-Lim Tan, Boon Chuan...
AGENTS
2001
Springer
15 years 4 months ago
A multi-agent system for automated genomic annotation
Massive amounts of raw data are currently being generated by biologists while sequencing organisms. Outside of the largest, high-pro le projects such as the Human Genome Project, ...
Keith Decker, Xiaojing Zheng, Carl Schmidt
GRC
2010
IEEE
15 years 28 days ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
ICML
1999
IEEE
16 years 19 days ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox