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JMLR
2010
129views more  JMLR 2010»
15 years 1 months ago
Expectation Truncation and the Benefits of Preselection In Training Generative Models
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Jörg Lücke, Julian Eggert
CAINE
2003
15 years 7 months ago
A Fuzzy Logic Based Multiple Reference Model Adaptive Control
This paper presents a fuzzy logic approach for switching multiple reference models, within the Model Reference Adaptive Control (MRAC) framework, in response to major changes in t...
Sukumar Kamalasadan, Adel A. Ghandakly, Khalid S. ...
BMCBI
2011
14 years 10 months ago
To aggregate or not to aggregate high-dimensional classifiers
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
CVPR
2007
IEEE
16 years 8 months ago
OPTIMOL: automatic Online Picture collecTion via Incremental MOdel Learning
A well-built dataset is a necessary starting point for advanced computer vision research. It plays a crucial role in evaluation and provides a continuous challenge to stateof-the-...
Li-Jia Li, Gang Wang, Fei-Fei Li 0002
ATAL
2009
Springer
16 years 1 months ago
Generalization risk minimization in empirical game models
Experimental analysis of agent strategies in multiagent systems presents a tradeoff between granularity and statistical confidence. Collecting a large amount of data about each s...
Patrick R. Jordan, Michael P. Wellman