We present a new machine learning approach to the inverse parametric sequence alignment problem: given as training examples a set of correct pairwise global alignments, find the p...
In this paper, we compare two distinct primal sketch feature extraction operators: one based on neural network feature learning and the other based on mathematical models of the f...
We discuss a Probably Approximate Correct (PAC) learning paradigm for Boolean formulas, which we call PAC meditation, where the class of formulas to be learnt is not known in advan...
Bruno Apolloni, Andrea Brega, Dario Malchiodi, Gio...
We present new fingerprint classification algorithms based on two machine learning approaches: support vector machines (SVMs), and recursive neural networks (RNNs). RNNs are traine...
Yuan Yao, Gian Luca Marcialis, Massimiliano Pontil...
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...