A fundamental problem in machine learning is to extract compact but relevant representations of empirical data. Relevance can be measured by the ability to make good decisions based on the representations, for example in terms of classification accuracy. Compact representations can lead to more human-interpretable models, as well as improve scalability. Furthermore, in multi-class and multi-tas...

Large Margin Transformation Learning

We present an improvement of Novikoff's perceptron convergence theorem. Reinterpreting this mistake bound as a margin dependent sparsity guarantee allows us to give a PAC-style generalisation error bound for the classifier learned by the perceptron learning algorithm. The bound value crucially depends on the margin a support vector machine would achieve on the same data set using the same kerne...

In this paper, we investigate the problem of exploiting global information to improve the performance of SVMs on large scale classification problems. We first present a unified general framework for the existing min-max machine methods in terms of within-class dispersions and between-class dispersions. By defining a new within-class dispersion measure, we then propose a novel max-margin ratio m...

We present a framework for margin based active learning of linear separators. We instantiate it for a few important cases, some of which have been previously considered in the literature. We analyze the effectiveness of our framework both in the realizable case and in a specific noisy setting related to the Tsybakov small noise condition.

The wings in different insect species are morphologically distinct with regards to their size, outer contour (margin) shape, venation, and pigmentation. The basis of the diversity of wing margin shapes remains unknown, despite the fact that gene networks governing the Drosophila wing development have been well characterised. Among the different types of wing margin shapes, smoothly curved conto...

the effect of 6-month water storage on microleakage of two-component self-etch adhesive systems      dr. mohammadibasir m .,1 dr. seyed tabaii e .2   1 assistant professor, department of operative dentistry , school of dentistry, shahed university. tehran , iran.   2 dentist.     (received 5 dec, 2010 accepted 14 april, 2011)     abstract     background and aim : simplification of the self-etch...