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JMLR
2012
12 years 9 days ago
Sparse Additive Machine
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
Tuo Zhao, Han Liu
ICMLA
2009
13 years 7 months ago
Improving Clinical Relevance in Ensemble Support Vector Machine Models of Radiation Pneumonitis Risk
Patients undergoing thoracic radiation therapy can develop radiation pneumonitis (RP), a potentially fatal inflammation of the lungs. Support vector machines (SVMs), a statistical...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...
JMLR
2010
139views more  JMLR 2010»
13 years 4 months ago
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
AIED
2011
Springer
13 years 1 months ago
Early Prediction of Cognitive Tool Use in Narrative-Centered Learning Environments
Narrative-centered learning environments introduce novel opportunities for supporting student problem solving and learning. By incorporating cognitive tools into plots and characte...
Lucy R. Shores, Jonathan P. Rowe, James C. Lester
CVPR
2008
IEEE
14 years 12 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher