IEEE transactions on neural networks and learning systems
Jan 17, 2018
Online learning has been successfully applied in various machine learning problems. Conventional analysis of online learning achieves a sharp generalization bound with a strongly convex assumption. In this paper, we study the generalization ability o...
Journal of magnetic resonance imaging : JMRI
Jan 17, 2018
BACKGROUND: Adrenal adenomas (AA) are the most common benign adrenal lesions, often characterized based on intralesional fat content as either lipid-rich (LRA) or lipid-poor (LPA). The differentiation of AA, particularly LPA, from nonadenoma adrenal ...
Deep neural networks (DNNs), which are kinds of the machine learning approaches, are powerful tools for analyzing big sets of data derived from biological and environmental systems. However, DNNs are not applicable to metabolomics studies because the...
Proceedings of the National Academy of Sciences of the United States of America
Jan 16, 2018
Protocell models are used to investigate how cells might have first assembled on Earth. Some, like oil-in-water droplets, can be seemingly simple models, while able to exhibit complex and unpredictable behaviors. How such simple oil-in-water systems ...
Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go). Less attention has been given to scenarios in which human-machine coo...
BACKGROUND: Biomedical ontologies pose several challenges to ontology matching due both to the complexity of the biomedical domain and to the characteristics of the ontologies themselves. The biomedical tracks in the Ontology Matching Evaluation Init...
Computational intelligence and neuroscience
Jan 15, 2018
This paper proposes an enhanced ant colony optimization with dynamic mutation and ad hoc initialization, ACODM-I, for improving the accuracy of Takagi-Sugeno-Kang- (TSK-) type fuzzy systems design. Instead of the generic initialization usually used i...
The aim of this study was to investigate if a machine learning algorithm utilizing triaxial accelerometer, gyroscope, and magnetometer data from an inertial motion unit (IMU) could detect surface- and age-related differences in walking. Seventeen old...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jan 12, 2018
Variable selection plays a key role in classification and multivariate calibration. Variable selection methods are aimed at choosing a set of variables, from a large pool of available predictors, relevant to the analyte concentrations estimation, or ...
International journal of medical informatics
Jan 12, 2018
BACKGROUND: In an era of "big data," computationally efficient and privacy-aware solutions for large-scale machine learning problems become crucial, especially in the healthcare domain, where large amounts of data are stored in different locations an...
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