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Energy-based learning models and their applications

Grant number: 16/19403-6
Support type:Regular Research Grants
Duration: August 01, 2017 - July 31, 2019
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:João Paulo Papa
Grantee:João Paulo Papa
Home Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil
Assoc. researchers:Aparecido Nilceu Marana ; Clayton Reginaldo Pereira ; Dinesh Kant Kumar ; Gustavo Kunde Rohde

Abstract

Energy-based models have been employed in a number of research areas, since they belong to a broad framework that comprises both probabilistic and non-probabilistic techniques. Among the most used techniques from this context, one can refer to the Restricted Boltzmann Machines and their deep learning-driven variants: Deep Belief Nets and Deep Boltzmann Machines. Such models also have shortcomings that will be considered in this proposal, such as the automatic optimization of their parameters, how to enhance the effectiveness of the learning process by means of sampling in Markov chains, as well as how to obtain a better regularization process based on different temperatures and pruning neurons. The proposal has two main lines of research: (i) applications and (ii) theoretic work. In the former, we will look for applications that have not evaluated the aforementioned energy-based models to date, mainly the ones related to biometric- and medicine-oriented data. In regard to the theoretic research, we expect to contribute with different models for sampling in Markov chains aiming at enhancing the inference step of these models. The proposal also considers national and foreign researchers, as well as undergraduate and graduate students. Since there are a very few research groups in Brazil that work in the same context of this proposal, we believe we can make difference and help the scientific community with works related to energy-based learning. (AU)

Scientific publications (25)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
RODRIGUES, DOUGLAS; DE ALBUQUERQUE, VICTOR HUGO C.; PAPA, JOAO PAULO. A multi-objective artificial butterfly optimization approach for feature selection. APPLIED SOFT COMPUTING, v. 94, SEP 2020. Web of Science Citations: 0.
DE ROSA, GUSTAVO H.; PAPA, JOAO P.; YANG, XIN-SHE. A nature-inspired feature selection approach based on hypercomplex information. APPLIED SOFT COMPUTING, v. 94, SEP 2020. Web of Science Citations: 0.
CULQUICONDOR, ALDO; BALDASSIN, ALEXANDRO; CASTELO-FERNANDEZ, CESAR; DE CARVALHO, JOAO P. L.; PAPA, JOAO PAULO. An efficient parallel implementation for training supervised optimum-path forest classifiers. Neurocomputing, v. 393, p. 259-268, JUN 14 2020. Web of Science Citations: 0.
COLOMBO, DANILO; ALVES LIMA, GILSON BRITO; PEREIRA, DANILLO ROBERTO; PAPA, JOAO P. Regression-based finite element machines for reliability modeling of downhole safety valves. RELIABILITY ENGINEERING & SYSTEM SAFETY, v. 198, JUN 2020. Web of Science Citations: 0.
RIBEIRO, LUIZ C. F.; AFONSO, LUIS C. S.; COLOMBO, DANILO; GUILHERME, IVAN R.; PAPA, JOAO P. Evolving Neural Conditional Random Fields for drilling report classification. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, v. 187, APR 2020. Web of Science Citations: 0.
SANTANA, MARCOS C. S.; PASSOS, JR., LEANDRO APARECIDO; MOREIRA, THIERRY P.; COLOMBO, DANILO; DE ALBUQUERQUE, VICTOR HUGO C.; PAPA, JOAO PAULO. A Novel Siamese-Based Approach for Scene Change Detection With Applications to Obstructed Routes in Hazardous Environments. IEEE INTELLIGENT SYSTEMS, v. 35, n. 1, p. 44-53, JAN-FEB 2020. Web of Science Citations: 0.
AMORIM, WILLIAN PARAGUASSU; ROSA, GUSTAVO HENRIQUE; THOMAZELLA, ROGERIO; COGO CASTANHO, JOSE EDUARDO; LOFRANO DOTTO, FABIO ROMANO; RODRIGUES JUNIOR, OSWALDO PONS; MARANA, APARECIDO NILCEU; PAPA, JOAO PAULO. Semi-supervised learning with connectivity-driven convolutional neural networks. PATTERN RECOGNITION LETTERS, v. 128, p. 16-22, DEC 1 2019. Web of Science Citations: 0.
AMORIM, WILLIAN PARAGUASSU; TETILA, EVERTON CASTELAO; PISTORI, HEMERSON; PAPA, JOAO PAULO. Semi-supervised learning with convolutional neural networks for UAV images automatic recognition. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 164, SEP 2019. Web of Science Citations: 0.
AFONSO, LUIS C. S.; ROSA, GUSTAVO H.; PEREIRA, CLAYTON R.; WEBER, SILKE A. T.; HOOK, CHRISTIAN; ALBUQUERQUE, VICTOR HUGO C.; PAPA, JOAO P. A recurrence plot-based approach for Parkinson's disease identification. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, v. 94, p. 282-292, MAY 2019. Web of Science Citations: 5.
FERNANDES, SILAS E. N.; PEREIRA, DANILLO R.; RAMOS, CAIO C. O.; SOUZA, ANDRE N.; GASTALDELLO, DANILO S.; PAPA, JOAO P. A Probabilistic Optimum-Path Forest Classifier for Non-Technical Losses Detection. IEEE TRANSACTIONS ON SMART GRID, v. 10, n. 3, p. 3226-3235, MAY 2019. Web of Science Citations: 1.
NACHIF FERNANDES, SILAS EVANDRO; PAPA, JOAO PAULO. Improving optimum-path forest learning using bag-of-classifiers and confidence measures. PATTERN ANALYSIS AND APPLICATIONS, v. 22, n. 2, p. 703-716, MAY 2019. Web of Science Citations: 1.
PEREIRA, CLAYTON R.; PEREIRA, DANILO R.; WEBER, SILKE A. T.; HOOK, CHRISTIAN; DE ALBUQUERQUE, VICTOR HUGO C.; PAPA, JOAO P. A survey on computer-assisted Parkinson's Disease diagnosis. ARTIFICIAL INTELLIGENCE IN MEDICINE, v. 95, p. 48-63, APR 2019. Web of Science Citations: 7.
DA COSTA, KELTON A. P.; PAPA, JOAO P.; LISBOA, CELSO O.; MUNOZ, ROBERTO; DE ALBUQUERQUE, VICTOR HUGO C. Internet of Things: A survey on machine learning-based intrusion detection approaches. Computer Networks, v. 151, p. 147-157, MAR 14 2019. Web of Science Citations: 6.
GUIMARAES, RANIERE ROCHA; PASSOS JR, LEANDRO A.; HOLANDA FILHO, RAIMIR; DE ALBUQUERQUE, VICTOR HUGO C.; RODRIGUES, JOEL J. P. C.; KOMAROV, MIKHAIL M.; PAPA, JOAO PAULO. Intelligent Network Security Monitoring Based on Optimum-Path Forest Clustering. IEEE NETWORK, v. 33, n. 2, p. 126-131, MAR-APR 2019. Web of Science Citations: 2.
KHOJASTEH, PARHAM; PASSOS JUNIOR, LEANDRO APARECIDO; CARVALHO, TIAGO; REZENDE, EDMAR; ALIAHMAD, BEHZAD; PAPA, JOAO PAULO; KUMAR, DINESH KANT. Exudate detection in fundus images using deeply-learnable features. COMPUTERS IN BIOLOGY AND MEDICINE, v. 104, p. 62-69, JAN 2019. Web of Science Citations: 6.
IWASHITA, ADRIANA SAYURI; PAPA, JOAO PAULO. An Overview on Concepts Drift Learning. IEEE ACCESS, v. 7, p. 1532-1547, 2019. Web of Science Citations: 0.
PAPA, JOAO P.; ROSA, GUSTAVO H.; DE SOUZA, ANDRE N.; AFONSO, LUIS C. S. Feature selection through binary brain storm optimization. COMPUTERS & ELECTRICAL ENGINEERING, v. 72, p. 468-481, NOV 2018. Web of Science Citations: 3.
PASSOS, JR., LEANDRO APARECIDO; PAPA, JOAO PAULO. Temperature-Based Deep Boltzmann Machines. NEURAL PROCESSING LETTERS, v. 48, n. 1, p. 95-107, AUG 2018. Web of Science Citations: 1.
SOUZA, LUIZ; OLIVEIRA, LUCIANO; PAMPLONA, MAURICIO; PAPA, JOAO. How far did we get in face spoofing detection?. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, v. 72, p. 368-381, JUN 2018. Web of Science Citations: 1.
DE SOUZA JR, LUIS A.; PALM, CHRISTOPH; MENDEL, ROBERT; HOOK, CHRISTIAN; EBIGBO, ALANNA; PROBST, ANDREAS; MESSMANN, HELMUT; WEBER, SILKE; PAPA, JOAO P. A survey on Barrett's esophagus analysis using machine learning. COMPUTERS IN BIOLOGY AND MEDICINE, v. 96, p. 203-213, MAY 1 2018. Web of Science Citations: 6.
PEREIRA, CLAYTON R.; PEREIRA, DANILO R.; ROSA, GUSTAVO H.; ALBUQUERQUE, VICTOR H. C.; WEBER, SILKE A. T.; HOOK, CHRISTIAN; PAPA, JOAO P. Handwritten dynamics dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification. ARTIFICIAL INTELLIGENCE IN MEDICINE, v. 87, p. 67-77, MAY 2018. Web of Science Citations: 15.
PEREIRA, DANILLO ROBERTO; PAPA, JOAO PAULO; ROSALIN SARAIVA, GUSTAVO FRANCISCO; SOUZA, GUSTAVO MAIA. Automatic classification of plant electrophysiological responses to environmental stimuli using machine learning and interval arithmetic. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 145, p. 35-42, FEB 2018. Web of Science Citations: 6.
ALYASSERI, ZAID ABDI ALKAREEM; KHADER, AHAMAD TAJUDIN; AL-BETAR, MOHAMMED AZMI; PAPA, JOAO P.; ALOMARI, OSAMA AHMAD. EEG Feature Extraction for Person Identification Using Wavelet Decomposition and Multi-Objective Flower Pollination Algorithm. IEEE ACCESS, v. 6, p. 76007-76024, 2018. Web of Science Citations: 4.
PAPA, JOAO PAULO; ROSA, GUSTAVO HENRIQUE; PAPA, LUCIENE PATRICI. A binary-constrained Geometric Semantic Genetic Programming for feature selection purposes. PATTERN RECOGNITION LETTERS, v. 100, p. 59-66, DEC 1 2017. Web of Science Citations: 3.
RODRIGUES, DOUGLAS; PAPA, JOAO P.; ADELI, HOJJAT. Meta-heuristic multi- and many-objective optimization techniques for solution of machine learning problems. EXPERT SYSTEMS, v. 34, n. 6 DEC 2017. Web of Science Citations: 2.

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