Gustavo Batista

Orcid: 0000-0002-3482-8442

Affiliations:
  • University of New South Wales, Sydney, Australia
  • University of Sao Paulo, Brazil (former)


According to our database1, Gustavo Batista authored at least 115 papers between 2000 and 2024.

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Bibliography

2024
Efficient IoT Traffic Inference: From Multi-view Classification to Progressive Monitoring.
ACM Trans. Internet Things, February, 2024

Towards Weaknesses and Attack Patterns Prediction for IoT Devices.
CoRR, 2024

Towards Detecting IoT Event Spoofing Attacks Using Time-Series Classification.
CoRR, 2024

AA-DLADMM: An Accelerated ADMM-based Framework for Training Deep Neural Networks.
CoRR, 2024

Poster: Understanding and Managing Changes in IoT Device Behaviors for Reliable Network Traffic Inference.
Proceedings of the ACM SIGCOMM 2024 Conference: Posters and Demos, 2024

Quantification Over Time.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

SAfER: Simplified Auto-encoder for (Anomalous) Event Recognition.
Proceedings of the 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things, 2024

Charting a Fair Path: FaGGM Fairness-Aware Generative Graphical Models.
Proceedings of the AI 2024: Advances in Artificial Intelligence, 2024

2023
Dynamic Inference From IoT Traffic Flows Under Concept Drifts in Residential ISP Networks.
IEEE Internet Things J., September, 2023

Detecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity.
CoRR, 2023

Quantifying and Managing Impacts of Concept Drifts on IoT Traffic Inference in Residential ISP Networks.
CoRR, 2023

MC-SQ: A Highly Accurate Ensemble for Multi-class Quantification.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Ensembles of Classifiers and Quantifiers with Data Fusion for Quantification Learning.
Proceedings of the Discovery Science - 26th International Conference, 2023

2022
Hierarchical classification of pollinating flying insects under changing environments.
Ecol. Informatics, 2022

AdIoTack: Quantifying and refining resilience of decision tree ensemble inference models against adversarial volumetric attacks on IoT networks.
Comput. Secur., 2022

Time Series Prediction via Similarity Search: Exploring Invariances, Distance Measures and Ensemble Functions.
IEEE Access, 2022

Classifying Time-Series of IoT Flow Activity using Deep Learning and Intransitive Features.
Proceedings of the 14th International Conference on Software, 2022

Update Compression for Deep Neural Networks on the Edge.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Geographic Context-Based Stacking Learning for Election Prediction from Socio-economic Data.
Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

2021
COVID-Safe Spatial Occupancy Monitoring Using OFDM-Based Features and Passive WiFi Samples.
ACM Trans. Manag. Inf. Syst., 2021

Analysing Spatio-Temporal Voting Patterns in Brazilian Elections Through a Simple Data Science Pipeline.
J. Inf. Data Manag., 2021

An Open-Source Tool for Classification Models in Resource-Constrained Hardware.
CoRR, 2021

A Graph-Based Spatial Cross-Validation Approach for Assessing Models Learned with Selected Features to Understand Election Results.
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Accurately Quantifying under Score Variability.
Proceedings of the IEEE International Conference on Data Mining, 2021

Passive WiFi CSI Sensing Based Machine Learning Framework for COVID-Safe Occupancy Monitoring.
Proceedings of the IEEE International Conference on Communications Workshops, 2021

Pitfalls in Quantification Assessment.
Proceedings of the CIKM 2021 Workshops co-located with 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), 2021

2020
Challenges in benchmarking stream learning algorithms with real-world data.
Data Min. Knowl. Discov., 2020

Quantifying With Only Positive Training Data.
CoRR, 2020

Melhorando a Acurácia da Detecção de Lavagem de Dinheiro na Rede Bitcoin.
Proceedings of the XXXVIII Brazilian Symposium on Computer Networks and Distributed Systems, 2020

A Combination of Local Approaches for Hierarchical Music Genre Classification.
Proceedings of the 21th International Society for Music Information Retrieval Conference, 2020

The Importance of the Test Set Size in Quantification Assessment.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Algorithm Recommendation for Data Streams.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Accurately Quantifying a Billion Instances per Second.
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

2019
Fast Similarity Matrix Profile for Music Analysis and Exploration.
IEEE Trans. Multim., 2019

Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model.
Inf. Sci., 2019

EmbML Tool: Supporting the use of Supervised Learning Algorithms in Low-Cost Embedded Systems.
Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

DyS: A Framework for Mixture Models in Quantification.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Combining instance selection and self-training to improve data stream quantification.
J. Braz. Comput. Soc., 2018

Speeding up similarity search under dynamic time warping by pruning unpromising alignments.
Data Min. Knowl. Discov., 2018

Unsupervised context switch for classification tasks on data streams with recurrent concepts.
Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

One-Class Quantification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

On the Need of Class Ratio Insensitive Drift Tests for Data Streams.
Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2018

Classifying and Counting with Recurrent Contexts.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Elastic Time Series Motifs and Discords.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

A Fuzzy Classifier for Data Streams with Infinitely Delayed Labels.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2018

Towards Hierarchical Classification of Data Streams.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2018

Evaluating Stream Classifiers with Delayed Labels Information.
Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

2017
Unsupervised active learning techniques for labeling training sets: An experimental evaluation on sequential data.
Intell. Data Anal., 2017

Quantification in Data Streams: Initial Results.
Proceedings of the 2017 Brazilian Conference on Intelligent Systems, 2017

2016
Speeding Up All-Pairwise Dynamic Time Warping Matrix Calculation.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

SiMPle: Assessing Music Similarity Using Subsequences Joins.
Proceedings of the 17th International Society for Music Information Retrieval Conference, 2016

Constrained Local and Global Consistency for semi-supervised learning.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Improved Time Series Classification with Representation Diversity and SVM.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

Prefix and Suffix Invariant Dynamic Time Warping.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015
Class imbalance revisited: a new experimental setup to assess the performance of treatment methods.
Knowl. Inf. Syst., 2015

Exploring Low Cost Laser Sensors to Identify Flying Insect Species - Evaluation of Machine Learning and Signal Processing Methods.
J. Intell. Robotic Syst., 2015

ENIAC 2013 Special Issue.
J. Intell. Robotic Syst., 2015

Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Music Shapelets for Fast Cover Song Recognition.
Proceedings of the 16th International Society for Music Information Retrieval Conference, 2015

Automatic classification of drum sounds with indefinite pitch.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

An experimental analysis on time series transductive classification on graphs.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Effective insect recognition using a stacked autoencoder with maximum correntropy criterion.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Time Series Classification with Representation Ensembles.
Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

Classification of Evolving Data Streams with Infinitely Delayed Labels.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

A Study of the Use of Complexity Measures in the Similarity Search Process Adopted by kNN Algorithm for Time Series Prediction.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

IGMM-CD: A Gaussian Mixture Classification Algorithm for Data Streams with Concept Drifts.
Proceedings of the 2015 Brazilian Conference on Intelligent Systems, 2015

2014
Coping with highly imbalanced datasets: A case study with definition extraction in a multilingual setting.
Nat. Lang. Eng., 2014

CID: an efficient complexity-invariant distance for time series.
Data Min. Knowl. Discov., 2014

Flying Insect Classification with Inexpensive Sensors.
CoRR, 2014

Music Classification by Transductive Learning Using Bipartite Heterogeneous Networks.
Proceedings of the 15th International Society for Music Information Retrieval Conference, 2014

Extracting Texture Features for Time Series Classification.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Time Series Transductive Classification on Imbalanced Data Sets: An Experimental Study.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Adding Diversity to Rank Examples in Anytime Nearest Neighbor Classification.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

2013
Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping.
ACM Trans. Knowl. Discov. Data, 2013

Influence of Graph Construction on Semi-supervised Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

DTW-D: time series semi-supervised learning from a single example.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

A Video Compression-Based Approach to Measure Music Structural Similarity.
Proceedings of the 14th International Society for Music Information Retrieval Conference, 2013

Applying Machine Learning and Audio Analysis Techniques to Insect Recognition in Intelligent Traps.
Proceedings of the 12th International Conference on Machine Learning and Applications, 2013

Time Series Classification Using Compression Distance of Recurrence Plots.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Classification of Data Streams Applied to Insect Recognition: Initial Results.
Proceedings of the Brazilian Conference on Intelligent Systems, 2013

An Empirical Comparison of Dissimilarity Measures for Time Series Classification.
Proceedings of the Brazilian Conference on Intelligent Systems, 2013

2012
A Complexity-Invariant Measure Based on Fractal Dimension for Time Series Classification.
Int. J. Nat. Comput. Res., 2012

A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Searching and mining trillions of time series subsequences under dynamic time warping.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

An Experimental Design to Evaluate Class Imbalance Treatment Methods.
Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

Spoken Digit Recognition in Portuguese Using Line Spectral Frequencies.
Proceedings of the Advances in Artificial Intelligence - IBERAMIA 2012, 2012

2011
A Survey on Graphical Methods for Classification Predictive Performance Evaluation.
IEEE Trans. Knowl. Data Eng., 2011

A hybrid approach to learn with imbalanced classes using evolutionary algorithms.
Log. J. IGPL, 2011

A Complexity-Invariant Distance Measure for Time Series.
Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

SIGKDD demo: sensors and software to allow computational entomology, an emerging application of data mining.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Towards Automatic Classification on Flying Insects Using Inexpensive Sensors.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

2010
A Study of the Influence of Rule Measures in Classifiers Induced by Evolutionary Algorithms.
IEEE Intell. Informatics Bull., 2010

Discovering Knowledge Rules with Multi-Objective Evolutionary Computing.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Classification of Live Moths Combining Texture, Color and Shape Primitives.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

2009
Data mining with imbalanced class distributions: concepts and methods.
Proceedings of the 4th Indian International Conference on Artificial Intelligence, 2009

2008
Missing Value Imputation Using a Semi-supervised Rank Aggregation Approach.
Proceedings of the Advances in Artificial Intelligence, 2008

A Study with Class Imbalance and Random Sampling for a Decision Tree Learning System.
Proceedings of the Artificial Intelligence in Theory and Practice II, 2008

Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules.
Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

2006
A Comparison of Methods for Rule Subset Selection Applied to Associative Classification.
Inteligencia Artif., 2006

2005
Multi-view Semi-supervised Learning: An Approach to Obtain Different Views from Text Datasets.
Proceedings of the Advances in Logic Based Intelligent Systems, 2005

Balancing Strategies and Class Overlapping.
Proceedings of the Advances in Intelligent Data Analysis VI, 2005

2004
A study of the behavior of several methods for balancing machine learning training data.
SIGKDD Explor., 2004

Learning with Class Skews and Small Disjuncts.
Proceedings of the Advances in Artificial Intelligence - SBIA 2004, 17th Brazilian Symposium on Artificial Intelligence, São Luis, Maranhão, Brazil, September 29, 2004

Class Imbalances versus Class Overlapping: An Analysis of a Learning System Behavior.
Proceedings of the MICAI 2004: Advances in Artificial Intelligence, 2004

Applying Genetic and Symbolic Learning Algorithms to Extract Rules from Artificial Neural Networks.
Proceedings of the MICAI 2004: Advances in Artificial Intelligence, 2004

Improving Rule Induction Precision for Automated Annotation by Balancing Skewed Data Sets.
Proceedings of the Knowledge Exploration in Life Science Informatics, 2004

2003
Data pre-processing for supervised machine learning.
PhD thesis, 2003

An Analysis of Four Missing Data Treatment Methods for Supervised Learning.
Appl. Artif. Intell., 2003

Balancing Training Data for Automated Annotation of Keywords: a Case Study.
Proceedings of the II Brazilian Workshop on Bioinformatics, 2003

2002
Splice Junction Recognition using Machine Learning Techniques.
Proceedings of the I Brazilian Workshop on Bioinformatics, 2002

The Influence of Noisy Patterns in the Performance of Learning Methods in the Splice Junction Recognition Problem.
Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

A Study of K-Nearest Neighbour as an Imputation Method.
Proceedings of the Soft Computing Systems - Design, Management and Applications, 2002

2000
Applying One-Sided Selection to Unbalanced Datasets.
Proceedings of the MICAI 2000: Advances in Artificial Intelligence, 2000


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