R. Mello

发表

Multi-Keyword ranked search based on mapping set matching in cloud ciphertext storage system

Kuan-Ching Li, Rodrigo Fernandes de Mello, Junhui He, 2020, Connect. Sci..

Exigency-based real-time scheduling policy to provide absolute QoS for web services

Lucas S. Casagrande, F. J. Monaco, R. Mello, 2007, 19th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD'07).

In-depth comparison of deep artificial neural network architectures on seismic events classification

R. Mello, J. Canário, Millaray Curilem, 2020 .

Feature extraction based on exponential-weighted higher-order local auto-correlation: an approach to improve data characterization

I. Stojmenovic, R. Mello, M. Albertini, 2015 .

Optimizing Distributed Data Access in Grid Environments by Using Artificial Intelligence Techniques

Laurence T. Yang, Rodrigo Fernandes de Mello, Evgueni Dodonov, 2007, ISPA.

Performance Evaluation of Route: A Load Balancing Algorithm for Grid Computing

Laurence T. Yang, Rodrigo Fernandes de Mello, Luciano José Senger, 2006, RITA.

Cross-modality co-attention networks for visual question answering

Dezhi Han, Rodrigo Fernandes de Mello, Kuan-Ching Li, 2021, Soft Computing.

Extracting and predicting the communication behaviour of parallel applications

Rodrigo Fernandes de Mello, Luciano José Senger, Evgueni Dodonov, 2009, Int. J. Parallel Emergent Distributed Syst..

Improving the performance and accuracy of time series modeling based on autonomic computing systems

Rodrigo Fernandes de Mello, R. Mello, 2011, J. Ambient Intell. Humaniz. Comput..

Unsupervised Change Detection in Data Streams

A. Carvalho, R. Mello, J. A. A. Filho, 2012 .

Message from HPSEC Workshop Co-chairs

Jack Dongarra, Nectarios Koziris, Thomas Rauber, 2006, ICPP Workshops.

Proceedings of the 3rd international conference on High Performance Computing and Communications

Ronald H. Perrott, Laurence T. Yang, Rodrigo Fernandes de Mello, 2007 .

Proceedings of the Third international conference on High Performance Computing and Communications

Ronald H. Perrott, Laurence T. Yang, Barbara M. Chapman, 2007 .

Proposal of a Tree Load Balancing Algorithm to Grid Computing Environments

Laurence T. Yang, Rodrigo Fernandes de Mello, Maria Stela Veludo de Paiva, 2004, IEICE Trans. Inf. Syst..

An On‐Line Approach for Classifying and Extracting Application Behavior on Linux

Laurence T. Yang, Marcos José Santana, Rodrigo Fernandes de Mello, 2006 .

TS-stream: clustering time series on data streams

Cássio M. M. Pereira, R. Mello, 2014, Journal of Intelligent Information Systems.

Unsupervised density-based behavior change detection in data streams

André Carlos Ponce de Leon Ferreira de Carvalho, João Gama, Rodrigo Fernandes de Mello, 2014, Intell. Data Anal..

Energy-based function to evaluate data stream clustering

Rodrigo Fernandes de Mello, Marcelo Keese Albertini, R. Mello, 2013, Adv. Data Anal. Classif..

Data stream dynamic clustering supported by Markov chain isomorphisms

Rodrigo Fernandes de Mello, Marcelo Keese Albertini, R. Mello, 2013, Intell. Data Anal..

Designing architectures of convolutional neural networks to solve practical problems

Rodrigo Fernandes de Mello, Martha Dais Ferreira, Luis Gustavo Nonato, 2018, Expert Syst. Appl..

Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

Kuan-Ching Li, Dezhi Han, Rodrigo Fernandes de Mello, 2020, Sensors.

A Survey on Semi-supervised Learning for Delayed Partially Labelled Data Streams pdf

Heitor Murilo Gomes, Jesse Read, Albert Bifet, 2021, ACM Comput. Surv..

Image indexing and retrieval using an ART‐2A neural network architecture

Laurence T. Yang, Rodrigo Fernandes de Mello, Josiane Maria Bueno, 2008, Int. J. Imaging Syst. Technol..

Model for Automatic Text Classification and Categorization for Image Indexing and Retrieval

Laurence T. Yang, Rodrigo Fernandes de Mello, Josiane Maria Bueno, 2007, The 2007 International Conference on Intelligent Pervasive Computing (IPC 2007).

On supervised learning to model and predict cattle weight in precision livestock breeding

Adriele Giaretta Biase, R. Mello, T. Albertini, 2022, Comput. Electron. Agric..

On Application Behavior Extraction and Prediction to Support and Improve Process Scheduling Decisions

Rodrigo Fernandes de Mello, Evgueni Dodonov, R. Mello, 2010 .

Ensuring Learning Guarantees on Concept Drift Detection with Statistical Learning Theory pdf

Lucas Pagliosa, Rodrigo Mello, R. Mello, 2020, ArXiv.

On learning guarantees to unsupervised concept drift detection on data streams

Rodrigo Fernandes de Mello, Albert Bifet, Yule Vaz, 2019, Expert Syst. Appl..

A New Memory Slowdown Model for the Characterization of Computing Systems

Laurence T. Yang, Kuan-Ching Li, Rodrigo Fernandes de Mello, 2007, PaCT.

Model for Simulation of Heterogeneous High-Performance Computing Environments

Rodrigo Fernandes de Mello, Luciano José Senger, R. Mello, 2006, VECPAR.

Supporting Optimal Phase Space Reconstructions Using Neural Network Architecture for Time Series Modeling pdf

Alexandru Telea, Lucas Pagliosa, Rodrigo Mello, 2020, ArXiv.

Time Series Decomposition Using Spring System Applied on Phase Spaces

Rodrigo Fernandes de Mello, Eduardo R. Hruschka, Ricardo Araújo Rios, 2018, 2018 7th Brazilian Conference on Intelligent Systems (BRACIS).

Semi-supervised time series classification on positive and unlabeled problems using cross-recurrence quantification analysis

Rodrigo Fernandes de Mello, Lucas de Carvalho Pagliosa, R. Mello, 2018, Pattern Recognit..

Multidimensional surrogate stability to detect data stream concept drift

Rodrigo Fernandes de Mello, Rosane Maria Maffei Vallim, Felipe S. L. G. Duarte, 2017, Expert Syst. Appl..

Applying a kernel function on time-dependent data to provide supervised-learning guarantees

Rodrigo Fernandes de Mello, Lucas de Carvalho Pagliosa, R. Mello, 2017, Expert Syst. Appl..

Using dynamical systems tools to detect concept drift in data streams

Rodrigo Fernandes de Mello, Ricardo Araújo Rios, Fausto Guzzo da Costa, 2016, Expert Syst. Appl..

Modelling distributed computing workloads to support the study of scheduling decisions

Rodrigo Fernandes de Mello, Paulo Henrique Ribeiro Gabriel, R. Mello, 2015, Int. J. Comput. Sci. Eng..

Persistent homology for time series and spatial data clustering

Rodrigo Fernandes de Mello, Cássio M. M. Pereira, R. Mello, 2015, Expert Syst. Appl..

An Accurate Flood Forecasting Model Using Wireless Sensor Networks and Chaos Theory: A Case Study with Real WSN Deployment in Brazil

Jo Ueyama, Eduardo M. Mendiondo, Gustavo Pessin, 2014, EANN.

Improving time series modeling by decomposing and analyzing stochastic and deterministic influences

Rodrigo Fernandes de Mello, Ricardo Araújo Rios, R. Mello, 2013, Signal Process..

Classification of time series generation processes using experimental tools: a survey and proposal of an automatic and systematic approach

Rodrigo Fernandes de Mello, Ricardo Araújo Rios, Renato Porfirio Ishii, 2011, Int. J. Comput. Sci. Eng..

Quantifying Features Using False Nearest Neighbors: An Unsupervised Approach

André Carlos Ponce de Leon Ferreira de Carvalho, Huan Liu, Rodrigo Fernandes de Mello, 2011, 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence.

Prediction of dynamical, nonlinear, and unstable process behavior

Laurence T. Yang, Rodrigo Fernandes de Mello, L. Yang, 2009, The Journal of Supercomputing.

Multi-Dimensional Dynamic Time Warping for Image Texture Similarity

Rodrigo Fernandes de Mello, Iker Gondra, R. Mello, 2008, SBIA.

On the Shattering Coefficient of Supervised Learning Algorithms pdf

Rodrigo Fernandes de Mello, R. Mello, 2019, ArXiv.

On the Complexity of Labeled Datasets

R. Mello, 2019, 1911.05461.

Computing the Shattering Coefficient of Supervised Learning Algorithms pdf

Rodrigo Fernandes de Mello, Moacir Antonelli Ponti, Carlos Henrique Grossi Ferreira, 2018, ArXiv.

Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos? pdf

Rodrigo Fernandes de Mello, Tiago S. Nazaré, Moacir A. Ponti, 2018, ArXiv.

A routing load balancing policy for grid computing environments

Laurence T. Yang, Rodrigo Fernandes de Mello, Luciano José Senger, 2006, 20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06).

A Network Evaluation for LAN, MAN and WAN Grid Environments

Laurence T. Yang, Rodrigo Fernandes de Mello, Evgueni Dodonov, 2005, EUC.

Min-heap-based scheduling algorithm: an approximation algorithm for homogeneous and heterogeneous distributed systems

Rodrigo Fernandes de Mello, Paulo Henrique Ribeiro Gabriel, Marcelo Keese Albertini, 2016, Int. J. Parallel Emergent Distributed Syst..

On Simulated Annealing for the Scheduling of Parallel Applications

Rodrigo Fernandes de Mello, Luciano José Senger, R. Mello, 2008, 2008 20th International Symposium on Computer Architecture and High Performance Computing.

A Complex Network-Based Approach for Job Scheduling in Grid Environments

Laurence T. Yang, Rodrigo Fernandes de Mello, Renato Porfirio Ishii, 2007, HPCC.

A Comparison of Clustering Algorithms for Data Streams

Rodrigo Fernandes de Mello, Cássio M. M. Pereira, R. Mello, 2011 .

Grid job scheduling using Route with Genetic Algorithm support

Laurence T. Yang, Rodrigo Fernandes de Mello, Luciano José Senger, 2008, Telecommun. Syst..

Assessing Supervised Learning Algorithms

Rodrigo Fernandes de Mello, Moacir Antonelli Ponti, R. Mello, 2018 .

Extraction and Classification of User Behavior

Laurence T. Yang, Rodrigo Fernandes de Mello, Matheus L. dos Santos, 2007, EUC.

A Self-Organizing Neural Network to Approach Novelty Detection

Rodrigo Fernandes de Mello, Marcelo Keese Albertini, R. Mello, 2010, Intelligent Systems for Automated Learning and Adaptation.

A self-organizing neural network for detecting novelties

Rodrigo Fernandes de Mello, Marcelo Keese Albertini, R. Mello, 2007, SAC '07.

Performance Evaluation of Distributed Data Access Optimization Approaches: Experiments versus Simulations

Vinicius de Freitas Reis, R. Mello, 2011 .

Estimating determinism rates to detect patterns in geospatial datasets

Holger Lange, Rodrigo Fernandes de Mello, Lael Parrott, 2015 .

A Brief Review on Machine Learning

Rodrigo Fernandes de Mello, Moacir Antonelli Ponti, R. Mello, 2018 .

Feature Scoring using Tree-Based Ensembles for Evolving Data Streams

Heitor Murilo Gomes, Rodrigo Fernandes de Mello, Albert Bifet, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Data Streams Are Time Series: Challenging Assumptions

Rodrigo Fernandes de Mello, Jesse Read, Tatiane Nogueira, 2020, BRACIS.

Applying Empirical Mode Decomposition and mutual information to separate stochastic and deterministic influences embedded in signals

Rodrigo Fernandes de Mello, Ricardo Araújo Rios, R. Mello, 2016, Signal Process..

A novel approach for distributed application scheduling based on prediction of communication events

Rodrigo Fernandes de Mello, Evgueni Dodonov, R. Mello, 2010, Future Gener. Comput. Syst..

Decomposing time series into deterministic and stochastic influences: A survey

Rodrigo Fernandes de Mello, Eduardo R. Hruschka, Ricardo Araújo Rios, 2019, Digit. Signal Process..

Improving Scheduling Decisions by Using Knowledge About Parallel Applications Resource Usage

Laurence T. Yang, Marcos José Santana, Rodrigo Fernandes de Mello, 2005, HPCC.

Data Clustering Using Topological Features

Rodrigo Fernandes de Mello, Cássio M. M. Pereira, R. Mello, 2014, 2014 Brazilian Conference on Intelligent Systems.

Autonomous CNN (AutoCNN): A data-driven approach to network architecture determination

Abhay M. S. Aradhya, R. Mello, Mahardhika Pratama, 2022, Inf. Sci..

Rodrigo Fernandes de Mello, Cássio M. M. Pereira, R. Mello, 2013, RITA.

Coarse-Refinement Dilemma: On Generalization Bounds for Data Clustering pdf

Rodrigo Fernandes de Mello, Yule Vaz, Carlos Henrique Grossi Ferreira, 2019, Expert Syst. Appl..

A Radial Basis Function Neural Network approach to detect novelties: Applications on health datasets

Cássio M. M. Pereira, R.F. de Mello, C.M.M. Pereira, 2009, 2009 Joint Conferences on Pervasive Computing (JCPC).

Unsupervised change detection in data streams: an application in music analysis

Rodrigo Fernandes de Mello, Rosane Maria Maffei Vallim, R. Mello, 2015, Progress in Artificial Intelligence.

Testing for Linear and Nonlinear Gaussian Processes in Nonstationary Time Series

Michael Small, Rodrigo Fernandes de Mello, Ricardo Araújo Rios, 2015, Int. J. Bifurc. Chaos.

Proposal of a new stability concept to detect changes in unsupervised data streams

Rodrigo Fernandes de Mello, Rosane Maria Maffei Vallim, R. Mello, 2014, Expert Syst. Appl..

RouteGA: A Grid Load Balancing Algorithm with Genetic Support

Laurence T. Yang, Rodrigo Fernandes de Mello, Luciano José Senger, 2007, 21st International Conference on Advanced Information Networking and Applications (AINA '07).

Machine Learning: A Practical Approach on the Statistical Learning Theory

Rodrigo Fernandes de Mello, Moacir Antonelli Ponti, R. Mello, 2018 .

An Online Data Access Prediction and Optimization Approach for Distributed Systems

Rodrigo Fernandes de Mello, Renato Porfirio Ishii, R. Mello, 2012, IEEE Transactions on Parallel and Distributed Systems.

Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles pdf

Fernando V. Paulovich, Gabriel D. Cantareira, Rodrigo F. Mello, 2021, ArXiv.

A Novel Approach to Quantify Novelty Levels Applied on Ubiquitous Music Distribution

Kuan-Ching Li, Rodrigo Fernandes de Mello, Marcelo Keese Albertini, 2008, 2008 IEEE Asia-Pacific Services Computing Conference.

In Search for the Optimization Algorithm

Rodrigo Fernandes de Mello, Moacir Antonelli Ponti, R. Mello, 2018 .

Statistical Learning Theory

Rodrigo Fernandes de Mello, Moacir Antonelli Ponti, R. Mello, 2018 .

A Systematic Literature Review on Decomposition Approaches to Estimate Time Series Components

Rodrigo Fernandes de Mello, Ricardo Araújo Rios, R. Mello, 2012 .

AN EMPIRICAL APPROACH USING SPECTRAL AND RECURRENCE ANALYSIS TO ESTIMATE TIME SERIES STOCHASTIC AND DETERMINISTIC COMPONENTS

Rodrigo Fernandes de Mello, Ricardo Araújo Rios, R. Mello, 2011 .

Time complexity evaluation of cover song identification algorithms

Rodrigo Fernandes de Mello, Martha Dais Ferreira, R. Mello, 2021 .

Measuring the Shattering coefficient of Decision Tree models

Rodrigo Fernandes de Mello, Albert Bifet, Chaitanya Manapragada, 2019, Expert Syst. Appl..

Compressed k-Nearest Neighbors Ensembles for Evolving Data Streams

Albert Bifet, Rodrigo Fernandes de Mello, Silviu Maniu, 2020, ECAI.

Variation Detection applied in User Signature Verification

Rodrigo Fernandes de Mello, Marcelo Keese Albertini, Matheus L. dos Santos, 2011, RITA.

Theoretical learning guarantees applied to acoustic modeling

S. Aluísio, R. Mello, C. Shulby, 2019, Journal of the Brazilian Computer Society.

Acoustic Modeling Using a Shallow CNN-HTSVM Architecture

Rodrigo Fernandes de Mello, Sandra M. Aluísio, Martha Dais Ferreira, 2017, 2017 Brazilian Conference on Intelligent Systems (BRACIS).