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» Learning SVMs from Sloppily Labeled Data
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AROBOTS
2011
13 years 4 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
JMLR
2010
117views more  JMLR 2010»
13 years 4 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
KDD
2010
ACM
286views Data Mining» more  KDD 2010»
13 years 7 months ago
Nonnegative shared subspace learning and its application to social media retrieval
Although tagging has become increasingly popular in online image and video sharing systems, tags are known to be noisy, ambiguous, incomplete and subjective. These factors can ser...
Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Tru...
COLING
2010
13 years 4 months ago
Enhanced Sentiment Learning Using Twitter Hashtags and Smileys
Automated identification of diverse sentiment types can be beneficial for many NLP systems such as review summarization and public media analysis. In some of these systems there i...
Dmitry Davidov, Oren Tsur, Ari Rappoport
PKDD
2010
Springer
212views Data Mining» more  PKDD 2010»
13 years 7 months ago
Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
ErHeng Zhong, Wei Fan, Qiang Yang, Olivier Versche...