Abstract. We present a method to find the exact maximal margin hyperplane for linear Support Vector Machines when a new (existing) component is added (removed) to (from) the inner...
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
Abstract. We have studied the spatiotemporal behaviour of threshold coupled chaotic neurons. We observe that the chaos is controlled by threshold activated coupling, and the system...
Manish Dev Shrimali, Guoguang He, Sudeshna Sinha, ...
In the human mind, high-order knowledge is categorically organized, yet the nature of its internal representation system is not well understood. While it has been traditionally con...