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ICML
2004
IEEE
15 years 10 months ago
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
Zhihua Zhang, Dit-Yan Yeung, James T. Kwok
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)
82
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INFOCOM
2008
IEEE
15 years 4 months ago
Minerva: Learning to Infer Network Path Properties
—Knowledge of the network path properties such as latency, hop count, loss and bandwidth is key to the performance of overlay networks, grids and p2p applications. Network operat...
Rita H. Wouhaybi, Puneet Sharma, Sujata Banerjee, ...
SCESM
2006
ACM
269views Algorithms» more  SCESM 2006»
15 years 3 months ago
Inferring operational requirements from scenarios and goal models using inductive learning
Goal orientation is an increasingly recognised Requirements Engineering paradigm. However, integration of goal modelling with operational models remains an open area for which the...
Dalal Alrajeh, Alessandra Russo, Sebastián ...

Book
519views
16 years 8 months ago
Information Theory, Inference, and Learning Algorithms
This book is aimed at senior undergraduates and graduate students in Engineering, Science, Mathematics, and Computing. It expects familiarity with calculus, probability theory, and...
David J. C. MacKay