Accurate prediction of survival rates of cancer patients is often key to stratify patients for prognosis and treatment. Survival prediction is often accomplished by the TNM system...
Dechang Chen, Kai Xing, Donald Henson, Li Sheng, A...
In this paper, a grey neuro-adaptive control algorithm is suggested for Antilock Braking Systems (ABS). The concept of grey system theory, which has a certain prediction capabilit...
Erdal Kayacan, Yesim Oniz, Okyay Kaynak, Andon V. ...
In this paper, we introduce two new formulations for multi-class multi-kernel relevance vector machines (mRVMs) that explicitly lead to sparse solutions, both in samples and in nu...
Theodoros Damoulas, Yiming Ying, Mark A. Girolami,...
In this work, a new learning paradigm called target selection is proposed, which can be used to test for associations between a single genetic variable and a multidimensional, qua...
Johannes Mohr, Sambu Seo, Imke Puis, Andreas Heinz...
We have designed a framework for content based appraisal of documents. Our motivation is to provide computer assisted support for answering several appraisal criteria according to...
In this paper, we propose to use hypergraphs as the model for images and pose image segmentation as a machine learning problem in which some pixels (called seeds) are labeled as t...
In this paper, a new method for detecting shot boundaries in video sequences using a late fusion technique is proposed. The method uses color histogram as the feature, and process...
In evolving applications, there is a need for the dynamic selection of algorithms or algorithm parameters. Such selection is hardly ever governed by exact theory, so intelligent r...
In order to overcome the computation and storage problem for large-scale data set, an efficient iterative method of Generalized Discriminant Analysis is proposed. Because sample v...
This paper treats the problem of distributed planning in general-sum stochastic games with communication when the model is known. Our main contribution is a novel, game theoretic ...