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» Adapting SVM Classifiers to Data with Shifted Distributions
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ACL
2010
13 years 7 months ago
A Study of Information Retrieval Weighting Schemes for Sentiment Analysis
Most sentiment analysis approaches use as baseline a support vector machines (SVM) classifier with binary unigram weights. In this paper, we explore whether more sophisticated fea...
Georgios Paltoglou, Mike Thelwall
IEAAIE
2004
Springer
14 years 2 months ago
Recognition of Emotional States in Spoken Dialogue with a Robot
For flexible interactions between a robot and humans, we address the issue of automatic recognition of human emotions during the interaction such as embarrassment, pleasure, and af...
Kazunori Komatani, Ryosuke Ito, Tatsuya Kawahara, ...
TNN
2010
234views Management» more  TNN 2010»
13 years 3 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
ICPR
2008
IEEE
14 years 10 months ago
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 9 months ago
Cross domain distribution adaptation via kernel mapping
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...