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Rodrigo Fernandes de Mello
Rodrigo Fernandes de Mello
Itaú Unibanco SA
Verified email at itau-unibanco.com.br
Title
Cited by
Cited by
Year
Machine learning: a practical approach on the statistical learning theory
RF Mello, MA Ponti
Springer, 2018
220*2018
Persistent homology for time series and spatial data clustering
CMM Pereira, RF de Mello
Expert Systems with Applications 42 (15-16), 6026-6038, 2015
902015
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
592010
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
502007
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
492019
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
492006
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
432020
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
422021
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
422016
Improving time series modeling by decomposing and analyzing stochastic and deterministic influences
RA Rios, RF De Mello
Signal Processing 93 (11), 3001-3013, 2013
412013
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
332018
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
332018
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
322006
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
292016
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
292012
TS-stream: clustering time series on data streams
CMM Pereira, RF De Mello
Journal of Intelligent Information Systems 42, 531-566, 2014
272014
An On‐Line Approach for Classifying and Extracting Application Behavior on Linux
LJ Senger, R Fernandes de Mello, MJ Santana, R Helena, C Santana, ...
High‐Performance Computing: Paradigm and Infrastructure, 381-401, 2005
262005
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
262005
Prediction of dynamical, nonlinear, and unstable process behavior
RF de Mello, LT Yang
The Journal of Supercomputing 49, 22-41, 2009
252009
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
232019
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