Learning from Negative Examples in Set-Expansion

Automatic visual categorization is critically dependent on labeled examples for supervised learning. As an alternative to traditional expert labeling, social-tagged multimedia is becoming a novel yet subjective and inaccurate source of learning ...

Humans sometimes experience negative emotions caused by electronic devices that impede their task(s). User experience researchers have examined technology-caused negative affect by collecting task performance metrics, user feedback, and/or human ...

Neural networks prove their usefulness mainly in solving difficult problems of estimation, identification, prediction or complex optimization. For finding a correct solution for the problem, the network must be trained with a comprehensive dataset, able ...