This paper is about the use of metric data structures in high-dimensionalor non-Euclidean space to permit cached sufficientstatisticsaccelerationsof learning algorithms. It has re...
In many decision making problems, a number of independent attributes or criteria are often used to individually rate an alternative from an agent’s local perspective and then th...
Extensive experimental evidence is required to study the impact of text categorization approaches on real data and to assess the performance within operational scenarios. In this ...
Roberto Basili, Alessandro Moschitti, Maria Teresa...
While it is widely understood that criminal miscreants are subverting large numbers of Internet-connected computers (e.g., for bots, spyware, SPAM forwarding), it is less well app...
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...