Rodrigo Fernandes de Mello
Cited by
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Machine Learning: A Practical Approach on the Statistical Learning Theory
Springer, 2018
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
Persistent homology for time series and spatial data clustering
CMM Pereira, RF de Mello
Expert Systems with Applications 42 (15-16), 6026-6038, 2015
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
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
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
Improving time series modeling by decomposing and analyzing stochastic and deterministic influences
RA Rios, RF De Mello
Signal Processing 93 (11), 3001-3013, 2013
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
An on-line approach for classifying and extracting application behavior on linux
L Senger, RF Mello, MJ Santana, RHC Santana
High performance computing: Paradigm and infrastructure, 381-401, 2006
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
Prediction of dynamical, nonlinear, and unstable process behavior
RF de Mello, LT Yang
The Journal of Supercomputing 49 (1), 22-41, 2009
Concentric radviz: Visual exploration of multi-task classification
JHP Ono, F Sikansi, DC Corrêa, FV Paulovich, A Paiva, LG Nonato
2015 28th SIBGRAPI Conference on Graphics, Patterns and Images, 165-172, 2015
TS-stream: clustering time series on data streams
CMM Pereira, RF De Mello
Journal of Intelligent Information Systems 42 (3), 531-566, 2014
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
Classification of time series generation processes using experimental tools: a survey and proposal of an automatic and systematic approach
RP Ishii, RA Rios, RF Mello
International Journal of Computational Science and Engineering 6 (4), 217-237, 2011
A new migration model based on the evaluation of processes load and lifetime on heterogeneous computing environments
RF De Mello, LJ Senger
16th Symposium on Computer Architecture and High Performance Computing, 222-227, 2004
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
Automatic text classification using an artificial neural network
RF de Mello, LJ Senger, LT Yang
High Performance Computational Science and Engineering, 215-238, 2005
Multi-dimensional dynamic time warping for image texture similarity
RF de Mello, I Gondra
Brazilian Symposium on Artificial Intelligence, 23-32, 2008
An adaptive and historical approach to optimize data access in grid computing environments
RP Ishii, RF de Mello
INFOCOMP Journal of Computer Science 10 (2), 26-43, 2011
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