Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
—This paper addresses pattern classification in the framework of domain adaptation by considering methods that solve problems in which training data are assumed to be available o...
Classification problems with a very large or unbounded set of output categories are common in many areas such as natural language and image processing. In order to improve accurac...
Ivan Titov, Alexandre Klementiev, Kevin Small, Dan...
Numerous data mining problems involve an investigation of associations between features in heterogeneous datasets, where different prediction models can be more suitable for differ...
Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Pan...
In some domains, Information Extraction (IE) from texts requires syntactic and semantic parsing. This analysis is computationally expensive and IE is potentially noisy if it applie...