: This paper describes a rather novel method for the supervised training of regression systems that can be an alternative to feedforward Artificial Neural Networks (ANNs) trained w...
Mark J. Embrechts, Dirk Devogelaere, Marcel Rijcka...
We describe a trainable and scalable summarization system which utilizes features derived from information retrieval, information extraction, and NLP techniques and on-line resour...
Chinatsu Aone, Mary Ellen Okurowski, James Gorlins...
A problem that is inherent to the development and efficient use of solvers is that of tuning parameters. The CP community has a long history of addressing this task automatically. ...
We revisit 26 meta-features typically used in the context of meta-learning for model selection. Using visual analysis and computational complexity considerations, we find 4 meta-f...
Abstract. Finding correlation clusters in the arbitrary subspaces of highdimensional data is an important and a challenging research problem. The current state-of-the-art correlati...