Development of Deep Belief Networks to support the diagnosis of psychiatric disord...
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| Author(s): |
Total Authors: 4
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| Affiliation: | [1] Sao Paulo State Univ, Dept Comp, Av Eng Luiz Edmundo Carrijo Coube 14-01, BR-17033360 Bauru, SP - Brazil
[2] Middlesex Univ, Sch Sci & Technol, London NW4 4BT - England
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | APPLIED SOFT COMPUTING; v. 60, p. 328-335, NOV 2017. |
| Web of Science Citations: | 6 |
| Abstract | |
Deep learning techniques have been paramount in the last years, mainly due to their outstanding results in a number of applications. In this paper, we address the issue of fine-tuning parameters of Deep Belief Networks by means of meta-heuristics in which real-valued decision variables are described by quaternions. Such approaches essentially perform optimization in fitness landscapes that are mapped to a different representation based on hypercomplex numbers that may generate smoother surfaces. We therefore can map the optimization process onto a new space representation that is more suitable to learning parameters. Also, we proposed two approaches based on Harmony Search and quaternions that outperform the state-of-the-art results obtained so far in three public datasets for the reconstruction of binary images. (C) 2017 Elsevier B.V. All rights reserved. (AU) | |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support type: | Research Projects - Thematic Grants |
| FAPESP's process: | 14/16250-9 - On the parameter optimization in machine learning techniques: advances and paradigms |
| Grantee: | João Paulo Papa |
| Support type: | Regular Research Grants |
| FAPESP's process: | 15/25739-4 - Ón The study of semantics ín deep learning models |
| Grantee: | Gustavo Henrique de Rosa |
| Support type: | Scholarships in Brazil - Master |