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» Modeling Classification and Inference Learning
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137
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SIAMIS
2011
14 years 7 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
103
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KDD
2007
ACM
190views Data Mining» more  KDD 2007»
16 years 28 days ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith
114
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Sparse coding and dictionary learning based on the MDL principle
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Ignacio Ramírez, Guillermo Sapiro
AAAI
2010
15 years 2 months ago
Efficient Belief Propagation for Utility Maximization and Repeated Inference
Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...
Aniruddh Nath, Pedro Domingos
RIAO
2000
15 years 1 months ago
Language sensitive text classification
It is a traditional belief that in order to scale-up to more effective retrieval and access methods modern Information Retrieval has to consider more the text content. The modalit...
Roberto Basili, Alessandro Moschitti, Maria Teresa...