This paper presents the results of an investigation into the use of machine learning methods for the identification of narcotics from Raman spectra. The classification of spectr...
Tom Howley, Michael G. Madden, Marie-Louise O'Conn...
In this report, we describe our development on the Max/MSP toolbox MnM dedicated to mapping between gesture and sound, and more generally to statistical and machine learning metho...
Record linkage is the process of determining that two records refer to the same entity. A key subprocess is evaluating how well the individual fields, or attributes, of the recor...
Steven Minton, Claude Nanjo, Craig A. Knoblock, Ma...
— Many information retrieval and machine learning methods have not evolved in order to be applied to the Web. Two main problems in applying some machine learning techniques for W...
Abstract. The practice of medicine is becoming increasingly evidencebased and clinical practice guidelines (CPGs) are necessary for advancing evidence-based medicine (EBM). We hypo...
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...
We propose machine learning methods for the estimation of deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspo...
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...