String kernels directly model sequence similarities without the necessity of extracting numerical features in a vector space. Since they better capture complex traits in the seque...
Abstract. We propose a new algorithm for estimating the causal structure that underlies the observed dependence among n (n ≥ 4) binary variables X1, . . . , Xn. Our inference pri...
This paper devises a novel kernel function for structured natural language data. In the field of Natural Language Processing, feature extraction consists of the following two ste...
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...