This paper presents a novel method for DNA microarray gridding based on Support Vector Machine (SVM) classifiers. It employs a set of soft-margin SVMs to estimate the lines of the ...
Dimitris G. Bariamis, Dimitris Maroulis, Dimitrios...
We present a method for utilizing unannotated sentences to improve a semantic parser which maps natural language (NL) sentences into their formal meaning representations (MRs). Gi...
A new class of Support Vector Machine (SVM) that is applicable to sequential-pattern recognition such as speech recognition is developed by incorporating an idea of non-linear tim...
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...
Data-driven learning based on shift reduce parsing algorithms has emerged dependency parsing and shown excellent performance to many Treebanks. In this paper, we investigate the e...