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» An Application Framework for Collaborative Learning
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111
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JMLR
2010
117views more  JMLR 2010»
14 years 10 months ago
Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
Many real world applications employ multivariate performance measures and each example can belong to multiple classes. The currently most popular approaches train an SVM for each ...
Xinhua Zhang, Thore Graepel, Ralf Herbrich
115
Voted
JMLR
2010
177views more  JMLR 2010»
14 years 10 months ago
Multitask Learning for Brain-Computer Interfaces
Brain-computer interfaces (BCIs) are limited in their applicability in everyday settings by the current necessity to record subjectspecific calibration data prior to actual use of...
Morteza Alamgir, Moritz Grosse-Wentrup, Yasemin Al...
192
Voted
ICCV
2011
IEEE
14 years 3 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
144
Voted
SIGIR
2009
ACM
15 years 10 months ago
Learning to recommend with social trust ensemble
As an indispensable technique in the field of Information Filtering, Recommender System has been well studied and developed both in academia and in industry recently. However, mo...
Hao Ma, Irwin King, Michael R. Lyu
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
16 years 10 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)