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ICML
2007
IEEE
15 years 10 months ago
Simple, robust, scalable semi-supervised learning via expectation regularization
Although semi-supervised learning has been an active area of research, its use in deployed applications is still relatively rare because the methods are often difficult to impleme...
Gideon S. Mann, Andrew McCallum
ECML
2005
Springer
15 years 3 months ago
Active Learning for Probability Estimation Using Jensen-Shannon Divergence
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
Prem Melville, Stewart M. Yang, Maytal Saar-Tsecha...
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AAAI
2008
15 years 6 hour ago
Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning
This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particu...
Arthur Guez, Robert D. Vincent, Massimo Avoli, Joe...
TMI
2008
162views more  TMI 2008»
14 years 9 months ago
Generalized Tensor-Based Morphometry of HIV/AIDS Using Multivariate Statistics on Deformation Tensors
Abstract--This paper investigates the performance of a new multivariate method for tensor-based morphometry (TBM). Statistics on Riemannian manifolds are developed that exploit the...
Natasha Lepore, Caroline A. Brun, Yi-Yu Chou, Ming...
IJON
2007
184views more  IJON 2007»
14 years 9 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen