Abstract. In this paper, we classify all of the finite p-groups with at most three non linear irreducible character kernels.

Many kernels for discretely structured data in the literature are designed within the framework of the convolution kernel and its generalization, the mapping kernel. The two most important advantages to use this framework are an easy-to-check criteria of positive definiteness of the resulting kernels and efficient computation based on the dynamic programming methodology. On the other hand, the ...

We present Random Partition Kernels, a new class of kernels derived by demonstrating a natural connection between random partitions of objects and kernels between those objects. We show how the construction can be used to create kernels from methods that would not normally be viewed as random partitions, such as Random Forest. To demonstrate the potential of this method, we propose two new kern...

Roasting nuts may alter their chemical composition leading to changes in their health benefits. However, the presence of testa may alleviate the negative effects of thermal treatments. Hence, this study aimed to explore the effects of roasting on kernel chemical quality and colour development of Canarium indicum and examine to what extent testa would protect kernels against damage from roasting...

Learning from complex data is becoming increasingly important, and graph kernels have recently evolved into a rapidly developing branch of learning on structured data. However, previously proposed kernels rely on having discrete node label information. In this paper, we explore the power of continuous node-level features for propagation-based graph kernels. Speci cally, propagation kernels expl...

Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pairs of nodes need to be compared. Thus, large parse trees, obtained from HTML documents or structured network data, render convolution kernels inapplicable. In this article, we propose an effective approximation techni...

We introduce a general family of kernels based on weighted transducers or rational relations, rational kernels, that can be used for analysis of variable-length sequences or more generally weighted automata, in applications such as computational biology or speech recognition. We show that rational kernels can be computed efficiently using a general algorithm of composition of weighted transduce...

Abstract Our aim in this article is to solve the composite fractional relaxation differential equation by using different definitions of non-integer order derivative operator $D_{t}^{\alpha }$ D t ? , more specifically we employ Caputo, Caputo–Fab...