Ordinal regression problem and general multi-class classification problem are important and on-going research subject in machine learning. Support vector ordinal regression machine (SVORM) is an effective method for ordinal regression problem and has been used to deal with general multi-class classification problem. Up to now it is always assumed implicitly that the training data are known exac...

Mass spectrometry-based untargeted metabolomics often results in the observation of hundreds to thousands of features that are differentially regulated between sample classes. A major challenge in interpreting the data is distinguishing metabolites that are causally associated with the phenotype of interest from those that are unrelated but altered in downstream pathways as an effect. To facili...

Second-order volumetric features (e.g. ridges, dents, bumps, etc) were previously defined to extend the SMS object modeling system. Here, we show that one can extract surface features from range data that can be described in this vocabulary of second-order features. The process is based on a classification of regions found by an approach based on local surface shape, and has a natural scale str...

Second-order volumetric features (e.g. ridges, dents, bumps, etc) were previously defined to extend the SMS object modeling system. Here, we show that one can extract surface features from range data that can be described in this vocabulary of second-order features. The process is based on a classification of regions found by an approach based on local surface shape, and has a natural scale str...

We wish to thank the management of the restaurant company for allowing the use of their corporate data in the case study and the simulations. In accordance with their requests we have not shown the actual years that the data relates to and we have approximated some of the descriptive statistics. We also wish to thank the AJPT reviewers and the editor, Dan Simunic, for their excellent comments. ...

Rules and ontologies can be used to enrich a database system with advanced data access capabilities. The success of this paradigm has led to a number of languages such as DL-Lite, Datalog+/and OWL RL. The two major approaches to answering queries under constraints expressed in such languages are forward-chaining (materialization) and backward-chaining (query rewriting). The latter is typically ...

We propose a convex optimization based strategy to deal with uncertainty in the observations of a classification problem. We assume that instead of a sample (xi, yi) a distribution over (xi, yi) is specified. In particular, we derive a robust formulation when the distribution is given by a normal distribution. It leads to Second Order Cone Programming formulation. Our method is applied to the p...

In this paper, we present a new way to derive low dimensional representations of functional MRI datasets. This is done by introducing a state-space formalism, where the state corresponds to the components whose dynamical structure is of interest. The rank of the selected state space is chosen by statistical comparison with null datasets. We study the validity of our estimation scheme on a synth...