2018
Authors
Silva, W; Pinto, JR; Cardoso, JS;
Publication
2018 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
Abstract
Ordinal classification is a specific and demanding task, where the aim is not only to increase accuracy, but to also capture the natural order between the classes, and penalize incorrect predictions by how much they deviate from this ranking. If an ordinal classifier must be able to comply with all these requirements, a suitable ordinal metric must be able to accurately measure its degree of compliance. However, the current metrics are unable to completely capture these considerations when assessing classification performance. Moreover, most suffer from sensitivity to imbalanced classes, very common in ordinal classification. In this paper, we propose two variants of a novel performance index that accounts for both accuracy and ranking in the performance assessment of ordinal classification, and is robust against imbalanced classes.
2018
Authors
Couto, R; Campos, JC;
Publication
2018 1ST INTERNATIONAL CONFERENCE ON GRAPHICS AND INTERACTION (ICGI 2018)
Abstract
Alloy supports reasoning about software designs in early development stages. It is composed of a modelling language and a tool that is able to find valid instances of the model. Alloy is able to produce graphical representations of analysis results, which is essential for their interpretation. In previous work we have improved the representations with the usage of layout managers. Here, we further extend that work by presenting the improvements on the approach, and by introducing a new case study to analyse the contribution of layout managers, and to support validation trough a user study.
2018
Authors
Torgo, L; Matwin, S; Weiss, G; Moniz, N; Branco, P;
Publication
International Workshop on Cost-Sensitive Learning, COST@SDM 2018, San Diego, California, USA, May 5, 2018
Abstract
2018
Authors
Sanchez Bermudez, J; Millour, F; Baron, F; van Boekel, R; Bourges, L; Duvert, G; Garcia, PJV; Gomes, N; Hofmann, KH; Henning, T; Isbell, JW; Lopez, B; Matter, A; Pott, JU; Schertl, D; Thiebaut, E; Weigelt, G; Young, J;
Publication
EXPERIMENTAL ASTRONOMY
Abstract
During the last two decades, the first generation of beam combiners at the Very Large Telescope Interferometer has proved the importance of optical interferometry for high-angular resolution astrophysical studies in the near- and mid-infrared. With the advent of 4-beam combiners at the VLTI, the u - v coverage per pointing increases significantly, providing an opportunity to use reconstructed images as powerful scientific tools. Therefore, interferometric imaging is already a key feature of the new generation of VLTI instruments, as well as for other interferometric facilities like CHARA and JWST. It is thus imperative to account for the current image reconstruction capabilities and their expected evolutions in the coming years. Here, we present a general overview of the current situation of optical interferometric image reconstruction with a focus on new wavelength-dependent information, highlighting its main advantages and limitations. As an Appendix we include several cookbooks describing the usage and installation of several state-of-the art image reconstruction packages. To illustrate the current capabilities of the software available to the community, we recovered chromatic images, from simulated MATISSE data, using the MCMC software SQUEEZE. With these images, we aim at showing the importance of selecting good regularization functions and their impact on the reconstruction.
2018
Authors
de Freitas, NB; Jacobina, CB; Cunha, MF; Mello, JPRA;
Publication
2018 IEEE Energy Conversion Congress and Exposition (ECCE)
Abstract
2018
Authors
Catalao, JPS; Siano, P; Li, F; Masoum, MAS; Aghaei, J;
Publication
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Abstract
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