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» On Learning with Integral Operators
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PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
15 years 5 months ago
Entropy and Margin Maximization for Structured Output Learning
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...
REALWSN
2010
15 years 4 months ago
Motes in the Jungle: Lessons Learned from a Short-Term WSN Deployment in the Ecuador Cloud Forest
We study the characteristics of the communication links of a wireless sensor network in a tropical cloud forest in Ecuador, in the context of a wildlife monitoring application. Thi...
Matteo Ceriotti, Matteo Chini, Amy L. Murphy, Gian...
IJON
2011
90views more  IJON 2011»
14 years 10 months ago
Fault tolerant machine learning for nanoscale cognitive radio
We introduce a machine learning based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanosc...
Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo
ICIP
2005
IEEE
16 years 8 months ago
Face hallucination through dual associative learning
In this paper, we propose a novel patch-based face hallucination framework, which employs a dual model to hallucinate different components associated with one facial image. Our mod...
Wei Liu, Dahua Lin, Xiaoou Tang
ICML
2009
IEEE
16 years 7 months ago
A majorization-minimization algorithm for (multiple) hyperparameter learning
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng