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Rodrigo Fernandes de Mello
Rodrigo Fernandes de Mello
Itaú Unibanco SA
Dirección de correo verificada de itau-unibanco.com.br
Título
Citado por
Citado por
Año
Machine learning: a practical approach on the statistical learning theory
RF Mello, MA Ponti
Springer, 2018
2052018
Persistent homology for time series and spatial data clustering
CMM Pereira, RF de Mello
Expert Systems with Applications 42 (15-16), 6026-6038, 2015
1312015
A Practical Approach on the Statistical Learning Theory
RF de Mello, MA Ponti
Springer, New York, USA, 2018
102*2018
Enhancing the sensor node localization algorithm based on improved DV-hop and DE algorithms in wireless sensor networks
D Han, Y Yu, KC Li, RF de Mello
Sensors 20 (2), 343, 2020
732020
On learning guarantees to unsupervised concept drift detection on data streams
RF de Mello, Y Vaz, CH Grossi, A Bifet
Expert Systems with Applications 117, 90-102, 2019
722019
A novel approach for distributed application scheduling based on prediction of communication events
E Dodonov, RF De Mello
Future Generation Computer Systems 26 (5), 740-752, 2010
602010
Multi-Keyword ranked search based on mapping set matching in cloud ciphertext storage system
T Xiao, D Han, J He, KC Li, RF de Mello
Connection Science 33 (1), 95-112, 2021
562021
A self-organizing neural network for detecting novelties
MK Albertini, RF de Mello
Proceedings of the 2007 ACM symposium on Applied computing, 462-466, 2007
522007
A routing load balancing policy for grid computing environments
RF de Mello, LJ Senger, LT Yang
20th International Conference on Advanced Information Networking and …, 2006
512006
Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos?
TS Nazare, RF de Mello, MA Ponti
arXiv preprint arXiv:1811.08495, 2018
502018
Applying empirical mode decomposition and mutual information to separate stochastic and deterministic influences embedded in signals
RA Rios, RF de Mello
Signal Processing 118, 159-176, 2016
502016
Improving time series modeling by decomposing and analyzing stochastic and deterministic influences
RA Rios, RF De Mello
Signal Processing 93 (11), 3001-3013, 2013
452013
In-depth comparison of deep artificial neural network architectures on seismic events classification
JP Canario, R Mello, M Curilem, F Huenupan, R Rios
Journal of Volcanology and Geothermal Research 401, 106881, 2020
422020
Designing architectures of convolutional neural networks to solve practical problems
MD Ferreira, DC Corrêa, LG Nonato, RF de Mello
Expert Systems with Applications 94, 205-217, 2018
392018
A survey on semi-supervised learning for delayed partially labelled data streams
HM Gomes, M Grzenda, R Mello, J Read, MH Le Nguyen, A Bifet
ACM Computing Surveys 55 (4), 1-42, 2022
362022
Decomposing time series into deterministic and stochastic influences: A survey
FSLG Duarte, RA Rios, ER Hruschka, RF de Mello
Digital Signal Processing 95, 102582, 2019
332019
Using dynamical systems tools to detect concept drift in data streams
FG da Costa, RA Rios, RF de Mello
Expert Systems with Applications 60, 39-50, 2016
332016
An On-Line Data Access Prediction and Optimization Approach for Distributed Systems
R Ishii, R Fernandes de Mello
Parallel and Distributed Systems, IEEE Transactions on 23 (6), 1017-1029, 2012
332012
A technique to reduce the test case suites for regression testing based on a self-organizing neural network architecture
ADS Simao, RF De Mello, LJ Senger
30th Annual International Computer Software and Applications Conference …, 2006
332006
Automatic text classification using an artificial neural network
RF de Mello, LJ Senger, LT Yang
High Performance Computational Science and Engineering: IFIP TC5 Workshop on …, 2005
302005
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Artículos 1–20