Applying One-Sided Selection to Unbalanced Datasets. - Gustavo E. A. P. A. Batista; André Carlos Ponce de Leon Ferreira de Carvalho; Maria Carolina Monard (MICAI, 2000)

A Study of K-Nearest Neighbour as an Imputation Method. - Gustavo E. A. P. A. Batista; Maria Carolina Monard (HIS, 2002)

The Influence of Noisy Patterns in the Performance of Learning Methods in the Splice Junction Recognition Problem. - Ana Carolina Lorena; Gustavo E. A. P. A. Batista; André Carlos Ponce de Leon Ferreira de Carvalho; Maria Carolina Monard (SBRN, 2002)

Splice Junction Recognition using Machine Learning Techniques. - Ana Carolina Lorena; Gustavo E. A. P. A. Batista; André Carlos Ponce de Leon Ferreira de Carvalho; Maria Carolina Monard (WOB, 2002)

Balancing Training Data for Automated Annotation of Keywords: a Case Study. - Gustavo E. A. P. A. Batista; Ana L. C. Bazzan; Maria Carolina Monard (WOB, 2003)

An Analysis of Four Missing Data Treatment Methods for Supervised Learning. - Gustavo E. A. P. A. Batista; Maria Carolina Monard (Appl. Artif. Intell., 2003)

Data pre-processing for supervised machine learning. - Gustavo Enrique De Almeida Prado Alves Batista (2003)

Improving Rule Induction Precision for Automated Annotation by Balancing Skewed Data Sets. - Gustavo E. A. P. A. Batista; Maria Carolina Monard; Ana L. C. Bazzan (KELSI, 2004)

Applying Genetic and Symbolic Learning Algorithms to Extract Rules from Artificial Neural Networks. - Claudia Regina Milaré; Gustavo E. A. P. A. Batista; André Carlos Ponce de Leon Ferreira de Carvalho; Maria Carolina Monard (MICAI, 2004)

Class Imbalances versus Class Overlapping: An Analysis of a Learning System Behavior. - Ronaldo C. Prati; Gustavo E. A. P. A. Batista; Maria Carolina Monard (MICAI, 2004)

Learning with Class Skews and Small Disjuncts. - Ronaldo C. Prati; Gustavo E. A. P. A. Batista; Maria Carolina Monard (SBIA, 2004)

A study of the behavior of several methods for balancing machine learning training data. - Gustavo E. A. P. A. Batista; Ronaldo C. Prati; Maria Carolina Monard (SIGKDD Explor., 2004)

Balancing Strategies and Class Overlapping. - Gustavo E. A. P. A. Batista; Ronaldo C. Prati; Maria Carolina Monard (IDA, 2005)

Multi-view Semi-supervised Learning: An Approach to Obtain Different Views from Text Datasets. - Edson Takashi Matsubara; Maria Carolina Monard; Gustavo E. A. P. A. Batista (LAPTEC, 2005)

A Comparison of Methods for Rule Subset Selection Applied to Associative Classification. - Gustavo E. A. P. A. Batista; Claudia Regina Milaré; Ronaldo Cristiano Prati; Maria Carolina Monard (Inteligencia Artif., 2006)

Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules. - Rafael Giusti; Gustavo E. A. P. A. Batista; Ronaldo Cristiano Prati (HIS, 2008)

A Study with Class Imbalance and Random Sampling for a Decision Tree Learning System. - Ronaldo C. Prati; Gustavo E. A. P. A. Batista; Maria Carolina Monard (IFIP AI, 2008)

Missing Value Imputation Using a Semi-supervised Rank Aggregation Approach. - Edson Takashi Matsubara; Ronaldo C. Prati; Gustavo E. A. P. A. Batista; Maria Carolina Monard (SBIA, 2008)

Data mining with imbalanced class distributions: concepts and methods. - Ronaldo C. Prati; Gustavo E. A. P. A. Batista; Maria Carolina Monard (IICAI, 2009)

Classification of Live Moths Combining Texture, Color and Shape Primitives. - Gustavo E. A. P. A. Batista; Bilson J. L. Campana; Eamonn J. Keogh (ICMLA, 2010)

Discovering Knowledge Rules with Multi-Objective Evolutionary Computing. - Rafael Giusti; Gustavo E. A. P. A. Batista (ICMLA, 2010)

A Study of the Influence of Rule Measures in Classifiers Induced by Evolutionary Algorithms. - Claudia Regina Milaré; Gustavo E. A. P. A. Batista; André C. P. L. F. de Carvalho (IEEE Intell. Informatics Bull., 2010)

Towards Automatic Classification on Flying Insects Using Inexpensive Sensors. - Gustavo E. A. P. A. Batista; Yuan Hao; Eamonn J. Keogh; Agenor Mafra-Neto (ICMLA (1), 2011)

SIGKDD demo: sensors and software to allow computational entomology, an emerging application of data mining. - Gustavo E. A. P. A. Batista; Eamonn J. Keogh; Agenor Mafra-Neto; Edgar Rowton (KDD, 2011)

A Complexity-Invariant Distance Measure for Time Series. - Gustavo E. A. P. A. Batista; Xiaoyue Wang 004; Eamonn J. Keogh (SDM, 2011)

A hybrid approach to learn with imbalanced classes using evolutionary algorithms. - Claudia Regina Milaré; Gustavo E. A. P. A. Batista; André C. P. L. F. de Carvalho (Log. J. IGPL, 2011)

A Survey on Graphical Methods for Classification Predictive Performance Evaluation. - Ronaldo C. Prati; Gustavo E. A. P. A. Batista; Maria Carolina Monard (IEEE Trans. Knowl. Data Eng., 2011)

Spoken Digit Recognition in Portuguese Using Line Spectral Frequencies. - Diego Furtado Silva; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista; Rafael Giusti (IBERAMIA, 2012)

An Experimental Design to Evaluate Class Imbalance Treatment Methods. - Gustavo Enrique De Almeida Prado Alves Batista; Diego Furtado Silva; Ronaldo Cristiano Prati (ICMLA (2), 2012)

Searching and mining trillions of time series subsequences under dynamic time warping. - Thanawin Rakthanmanon; Bilson J. L. Campana; Abdullah Mueen; Gustavo E. A. P. A. Batista; M. Brandon Westover; Qiang Zhu 002; Jesin Zakaria; Eamonn J. Keogh (KDD, 2012)

A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets. - Qiang Zhu 002; Gustavo E. A. P. A. Batista; Thanawin Rakthanmanon; Eamonn J. Keogh (SDM, 2012)

A Complexity-Invariant Measure Based on Fractal Dimension for Time Series Classification. - Ronaldo C. Prati; Gustavo E. A. P. A. Batista (Int. J. Nat. Comput. Res., 2012)

An Empirical Comparison of Dissimilarity Measures for Time Series Classification. - Rafael Giusti; Gustavo E. A. P. A. Batista (BRACIS, 2013)

Classification of Data Streams Applied to Insect Recognition: Initial Results. - Vinícius M. A. de Souza; Diego Furtado Silva; Gustavo E. A. P. A. Batista (BRACIS, 2013)

Time Series Classification Using Compression Distance of Recurrence Plots. - Diego Furtado Silva; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista (ICDM, 2013)

Applying Machine Learning and Audio Analysis Techniques to Insect Recognition in Intelligent Traps. - Diego Furtado Silva; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista; Eamonn J. Keogh; Daniel P. W. Ellis (ICMLA (1), 2013)

A Video Compression-Based Approach to Measure Music Structural Similarity. - Diego Furtado Silva; Hélène Papadopoulos; Gustavo Enrique De Almeida Prado Alves Batista; Daniel P. W. Ellis (ISMIR, 2013)

DTW-D: time series semi-supervised learning from a single example. - Yanping Chen 005; Bing Hu 001; Eamonn J. Keogh; Gustavo E. A. P. A. Batista (KDD, 2013)

Influence of Graph Construction on Semi-supervised Learning. - Celso André R. de Sousa; Solange O. Rezende; Gustavo E. A. P. A. Batista (ECML/PKDD (3), 2013)

Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping. - Thanawin Rakthanmanon; Bilson J. L. Campana; Abdullah Mueen; Gustavo E. A. P. A. Batista; M. Brandon Westover; Qiang Zhu 002; Jesin Zakaria; Eamonn J. Keogh (ACM Trans. Knowl. Discov. Data, 2013)

Adding Diversity to Rank Examples in Anytime Nearest Neighbor Classification. - Cristiano Inácio Lemes; Diego Furtado Silva; Gustavo E. A. P. A. Batista (ICMLA, 2014)

Time Series Transductive Classification on Imbalanced Data Sets: An Experimental Study. - Celso André R. de Sousa; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista (ICPR, 2014)

Extracting Texture Features for Time Series Classification. - Vinícius M. A. de Souza; Diego Furtado Silva; Gustavo E. A. P. A. Batista (ICPR, 2014)

Music Classification by Transductive Learning Using Bipartite Heterogeneous Networks. - Diego Furtado Silva; Rafael Geraldeli Rossi; Solange Oliveira Rezende; Gustavo Enrique De Almeida Prado Alves Batista (ISMIR, 2014)

Flying Insect Classification with Inexpensive Sensors. - Yanping Chen 005; Adena Why; Gustavo E. A. P. A. Batista; Agenor Mafra-Neto; Eamonn J. Keogh (CoRR, 2014)

CID: an efficient complexity-invariant distance for time series. - Gustavo E. A. P. A. Batista; Eamonn J. Keogh; Oben Moses Tataw; Vinícius M. A. de Souza (Data Min. Knowl. Discov., 2014)

Coping with highly imbalanced datasets: A case study with definition extraction in a multilingual setting. - Rosa Del Gaudio; Gustavo E. A. P. A. Batista; António Branco (Nat. Lang. Eng., 2014)

IGMM-CD: A Gaussian Mixture Classification Algorithm for Data Streams with Concept Drifts. - Luan Soares Oliveira; Gustavo E. A. P. A. Batista (BRACIS, 2015)

A Study of the Use of Complexity Measures in the Similarity Search Process Adopted by kNN Algorithm for Time Series Prediction. - Antonio Rafael Sabino Parmezan; Gustavo E. A. P. A. Batista (ICMLA, 2015)

Classification of Evolving Data Streams with Infinitely Delayed Labels. - Vinícius M. A. de Souza; Diego Furtado Silva; Gustavo E. A. P. A. Batista; João Gama 001 (ICMLA, 2015)

Time Series Classification with Representation Ensembles. - Rafael Giusti; Diego Furtado Silva; Gustavo E. A. P. A. Batista (IDA, 2015)

Effective insect recognition using a stacked autoencoder with maximum correntropy criterion. - Yu Qi; Goktug T. Cinar; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista; Yueming Wang 001; José C. Príncipe (IJCNN, 2015)

An experimental analysis on time series transductive classification on graphs. - Celso André R. de Sousa; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista (IJCNN, 2015)

Automatic classification of drum sounds with indefinite pitch. - Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista; Nilson E. Souza-Filho (IJCNN, 2015)

Music Shapelets for Fast Cover Song Recognition. - Diego Furtado Silva; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista (ISMIR, 2015)

Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency. - Vinícius M. A. de Souza; Diego Furtado Silva; João Gama 001; Gustavo E. A. P. A. Batista (SDM, 2015)

ENIAC 2013 Special Issue. - Gustavo E. A. P. A. Batista; Myriam Regattieri Delgado; Flávia Cristina Bernardini (J. Intell. Robotic Syst., 2015)

Exploring Low Cost Laser Sensors to Identify Flying Insect Species - Evaluation of Machine Learning and Signal Processing Methods. - Diego Furtado Silva; Vinícius M. A. de Souza; Daniel P. W. Ellis; Eamonn J. Keogh; Gustavo E. A. P. A. Batista (J. Intell. Robotic Syst., 2015)

Class imbalance revisited: a new experimental setup to assess the performance of treatment methods. - Ronaldo C. Prati; Gustavo E. A. P. A. Batista; Diego Furtado Silva (Knowl. Inf. Syst., 2015)

Prefix and Suffix Invariant Dynamic Time Warping. - Diego Furtado Silva; Gustavo E. A. P. A. Batista; Eamonn J. Keogh (ICDM, 2016)

Improved Time Series Classification with Representation Diversity and SVM. - Rafael Giusti; Diego Furtado Silva; Gustavo E. A. P. A. Batista (ICMLA, 2016)

Constrained Local and Global Consistency for semi-supervised learning. - Celso André R. de Sousa; Gustavo E. A. P. A. Batista (ICPR, 2016)

SiMPle: Assessing Music Similarity Using Subsequences Joins. - Diego Furtado Silva; Chin-Chia Michael Yeh; Gustavo E. A. P. A. Batista; Eamonn J. Keogh (ISMIR, 2016)

Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test. - Denis Moreira dos Reis; Peter A. Flach; Stan Matwin; Gustavo E. A. P. A. Batista (KDD, 2016)

Speeding Up All-Pairwise Dynamic Time Warping Matrix Calculation. - Diego Furtado Silva; Gustavo E. A. P. A. Batista (SDM, 2016)

Quantification in Data Streams: Initial Results. - André Gustavo Maletzke; Denis Moreira dos Reis; Gustavo E. A. P. A. Batista (BRACIS, 2017)

Unsupervised active learning techniques for labeling training sets: An experimental evaluation on sequential data. - Vinícius Mourão Alves de Souza; Rafael Geraldeli Rossi; Gustavo E. A. P. A. Batista; Solange O. Rezende (Intell. Data Anal., 2017)

Evaluating Stream Classifiers with Delayed Labels Information. - Vinícius M. A. de Souza; Tiago Pinho da Silva; Gustavo E. A. P. A. Batista (BRACIS, 2018)

Towards Hierarchical Classification of Data Streams. - Antonio Rafael Sabino Parmezan; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista (CIARP, 2018)

A Fuzzy Classifier for Data Streams with Infinitely Delayed Labels. - Tiago Pinho da Silva; Vinícius Mourão Alves de Souza; Gustavo Enrique De Almeida Prado Alves Batista; Heloisa de Arruda Camargo (CIARP, 2018)

Elastic Time Series Motifs and Discords. - Diego Furtado Silva; Gustavo E. A. P. A. Batista (ICMLA, 2018)

Classifying and Counting with Recurrent Contexts. - Denis Moreira dos Reis; André Gustavo Maletzke; Diego Furtado Silva; Gustavo E. A. P. A. Batista (KDD, 2018)

On the Need of Class Ratio Insensitive Drift Tests for Data Streams. - André Gustavo Maletzke; Denis Moreira dos Reis; Everton Alvares Cherman; Gustavo E. A. P. A. Batista (LIDTA@ECML/PKDD, 2018)

One-Class Quantification. - Denis Moreira dos Reis; André Gustavo Maletzke; Everton Alvares Cherman; Gustavo Enrique De Almeida Prado Alves Batista (ECML/PKDD (1), 2018)

Unsupervised context switch for classification tasks on data streams with recurrent concepts. - Denis Moreira dos Reis; André Gustavo Maletzke; Gustavo E. A. P. A. Batista (SAC, 2018)

Speeding up similarity search under dynamic time warping by pruning unpromising alignments. - Diego Furtado Silva; Rafael Giusti; Eamonn J. Keogh; Gustavo E. A. P. A. Batista (Data Min. Knowl. Discov., 2018)

Combining instance selection and self-training to improve data stream quantification. - André Gustavo Maletzke; Denis Moreira dos Reis; Gustavo E. A. P. A. Batista (J. Braz. Comput. Soc., 2018)

DyS: A Framework for Mixture Models in Quantification. - André Gustavo Maletzke; Denis Moreira dos Reis; Everton Alvares Cherman; Gustavo E. A. P. A. Batista (AAAI, 2019)

EmbML Tool: Supporting the use of Supervised Learning Algorithms in Low-Cost Embedded Systems. - Lucas Tsutsui da Silva; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista (ICTAI, 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. - Antonio Rafael Sabino Parmezan; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista (Inf. Sci., 2019)

Fast Similarity Matrix Profile for Music Analysis and Exploration. - Diego Furtado Silva; Chin-Chia Michael Yeh; Yan Zhu 014; Gustavo E. A. P. A. Batista; Eamonn J. Keogh (IEEE Trans. Multim., 2019)

Accurately Quantifying a Billion Instances per Second. - Waqar Hassan; André Gustavo Maletzke; Gustavo E. A. P. A. Batista (DSAA, 2020)

Algorithm Recommendation for Data Streams. - Jáder M. C. de Sá; André L. D. Rossi; Gustavo E. A. P. A. Batista; Luís Paulo F. Garcia (ICPR, 2020)

The Importance of the Test Set Size in Quantification Assessment. - André Gustavo Maletzke; Waqar Hassan; Denis Moreira dos Reis; Gustavo E. A. P. A. Batista (IJCAI, 2020)

A Combination of Local Approaches for Hierarchical Music Genre Classification. - Antonio Rafael Sabino Parmezan; Diego Furtado Silva; Gustavo E. A. P. A. Batista (ISMIR, 2020)

Melhorando a Acurácia da Detecção de Lavagem de Dinheiro na Rede Bitcoin. - Gabriel A. F. Rebello; Yining Hu 001; Kanchana Thilakarathna; Gustavo Batista; Aruna Seneviratne; Otto Carlos Muniz Bandeira Duarte (SBRC, 2020)

Quantifying With Only Positive Training Data. - Denis Moreira dos Reis; Marcílio de Souto; Elaine P. M. de Sousa; Gustavo E. A. P. A. Batista (CoRR, 2020)

Challenges in benchmarking stream learning algorithms with real-world data. - Vinícius M. A. de Souza; Denis Moreira dos Reis; André Gustavo Maletzke; Gustavo E. A. P. A. Batista (Data Min. Knowl. Discov., 2020)

Pitfalls in Quantification Assessment. - Waqar Hassan; André Gustavo Maletzke; Gustavo Batista (CIKM Workshops, 2021)

Passive WiFi CSI Sensing Based Machine Learning Framework for COVID-Safe Occupancy Monitoring. - Aryan Sharma; Junye Li 003; Deepak Mishra 001; Gustavo Batista; Aruna Seneviratne (ICC Workshops, 2021)

Accurately Quantifying under Score Variability. - André Gustavo Maletzke; Denis Moreira dos Reis; Waqar Hassan; Gustavo Batista (ICDM, 2021)

A Graph-Based Spatial Cross-Validation Approach for Assessing Models Learned with Selected Features to Understand Election Results. - Tiago Pinho da Silva; Antonio Rafael Sabino Parmezan; Gustavo E. A. P. A. Batista (ICMLA, 2021)

An Open-Source Tool for Classification Models in Resource-Constrained Hardware. - Lucas Tsutsui da Silva; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista (CoRR, 2021)

Analysing Spatio-Temporal Voting Patterns in Brazilian Elections Through a Simple Data Science Pipeline. - L. H. M. Jacintho; Tiago Pinho da Silva; Antonio Rafael Sabino Parmezan; Gustavo E. A. P. A. Batista (J. Inf. Data Manag., 2021)

COVID-Safe Spatial Occupancy Monitoring Using OFDM-Based Features and Passive WiFi Samples. - Junye Li 003; Aryan Sharma; Deepak Mishra 001; Gustavo Batista; Aruna Seneviratne (ACM Trans. Manag. Inf. Syst., 2021)

Geographic Context-Based Stacking Learning for Election Prediction from Socio-economic Data. - Tiago Pinho da Silva; Antonio Rafael Sabino Parmezan; Gustavo E. A. P. A. Batista (BRACIS (1), 2022)

Update Compression for Deep Neural Networks on the Edge. - Bo Chen 009; Ali Bakhshi; Gustavo Batista; Brian Wai-Him Ng; Tat-Jun Chin (CVPR Workshops, 2022)

Classifying Time-Series of IoT Flow Activity using Deep Learning and Intransitive Features. - Daravichet Tin; Maryam Shahpasand; Hassan Habibi Gharakheili; Gustavo Batista (SKIMA, 2022)

Time Series Prediction via Similarity Search: Exploring Invariances, Distance Measures and Ensemble Functions. - Antonio Rafael Sabino Parmezan; Vinícius M. A. de Souza; Gustavo E. A. P. A. Batista (IEEE Access, 2022)

AdIoTack: Quantifying and refining resilience of decision tree ensemble inference models against adversarial volumetric attacks on IoT networks. - Arman Pashamokhtari; Gustavo Batista; Hassan Habibi Gharakheili (Comput. Secur., 2022)

Hierarchical classification of pollinating flying insects under changing environments. - Antonio Rafael Sabino Parmezan; Vinícius M. A. de Souza; Arpita Seth; Indre Zliobaite; Gustavo E. A. P. A. Batista (Ecol. Informatics, 2022)

Ensembles of Classifiers and Quantifiers with Data Fusion for Quantification Learning. - Adriane Beatriz de Souza Serapião; Zahra Donyavi; Gustavo Batista (DS, 2023)

MC-SQ: A Highly Accurate Ensemble for Multi-class Quantification. - Zahra Donyavi; Adriane Serapio; Gustavo Batista (SDM, 2023)

Quantifying and Managing Impacts of Concept Drifts on IoT Traffic Inference in Residential ISP Networks. - Arman Pashamokhtari; Norihiro Okui; Masataka Nakahara; Ayumu Kubota; Gustavo Batista; Hassan Habibi Gharakheili (CoRR, 2023)

Detecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity. - Ayyoob Hamza; Hassan Habibi Gharakheili; Theophilus A. Benson; Gustavo Batista; Vijay Sivaraman (CoRR, 2023)

Dynamic Inference From IoT Traffic Flows Under Concept Drifts in Residential ISP Networks. - Arman Pashamokhtari; Norihiro Okui; Masataka Nakahara; Ayumu Kubota; Gustavo Batista; Hassan Habibi Gharakheili (IEEE Internet Things J., 2023)

Charting a Fair Path: FaGGM Fairness-Aware Generative Graphical Models. - Vivian Wei Jiang; Gustavo Batista; Michael Bain 001 (AI (1), 2024)

SAfER: Simplified Auto-encoder for (Anomalous) Event Recognition. - Yuvin Perera; Gustavo Batista; Wen Hu 001; Salil S. Kanhere; Sanjay K. Jha (DCOSS-IoT, 2024)

Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. - Honghui Wang; Weiming Zhi; Gustavo Batista; Rohitash Chandra (ICRA, 2024)

Quantification Over Time. - Feiyu Li; Hassan Habibi Gharakheili; Gustavo Batista (ECML/PKDD (5), 2024)

Poster: Understanding and Managing Changes in IoT Device Behaviors for Reliable Network Traffic Inference. - Shayan Azizi; Norihiro Okui; Masataka Nakahara; Ayumu Kubota; Gustavo Batista; Hassan Habibi Gharakheili (SIGCOMM (Posters and Demos), 2024)

Towards Weaknesses and Attack Patterns Prediction for IoT Devices. - Carlos A. Rivera Alvarez; Arash Shaghaghi; Gustavo Batista; Salil S. Kanhere (SIN, 2024)

AA-DLADMM: An Accelerated ADMM-based Framework for Training Deep Neural Networks. - Zeinab Ebrahimi; Gustavo Batista; Mohammad Deghat (CoRR, 2024)

Towards Detecting IoT Event Spoofing Attacks Using Time-Series Classification. - Uzma Maroof; Gustavo Batista; Arash Shaghaghi; Sanjay K. Jha (CoRR, 2024)

MC-SQ and MC-MQ: Ensembles for Multi-Class Quantification. - Zahra Donyavi; Adriane Beatriz de Souza Serapião; Gustavo Batista (IEEE Trans. Knowl. Data Eng., 2024)

Efficient IoT Traffic Inference: From Multi-view Classification to Progressive Monitoring. - Arman Pashamokhtari; Gustavo Batista; Hassan Habibi Gharakheili (ACM Trans. Internet Things, 2024)

Predicting IoT Device Vulnerability Fix Times with Survival and Failure Time Models. - Carlos Alberto Rivera Alvarez; Xinzhang Chen; Arash Shaghaghi; Gustavo Batista; Salil S. Kanhere (ACSW, 2025)

Revisit Time Series Classification Benchmark: The Impact of Temporal Information for Classification. - Yunrui Zhang; Gustavo Batista; Salil S. Kanhere (PAKDD (4), 2025)

Label Shift Estimation With Incremental Prior Update. - Yunrui Zhang; Gustavo Batista; Salil S. Kanhere (SDM, 2025)

FastFlow: Early Yet Robust Network Flow Classification using the Minimal Number of Time-Series Packets. - Rushi Jayeshkumar Babaria; Minzhao Lyu; Gustavo Batista; Vijay Sivaraman (SIGMETRICS (Abstracts), 2025)

MetaQuant: A framework for metaheuristic based quantification. - Adriane Beatriz de Souza Serapião; Zahra Donyavi; Gustavo Batista (Appl. Soft Comput., 2025)

Pedestrian trajectory prediction using goal-driven and dynamics-based deep learning framework. - Honghui Wang; Weiming Zhi; Gustavo Batista; Rohitash Chandra (Expert Syst. Appl., 2025)

AA-mDLAM: An accelerated ADMM-based framework for training deep neural networks. - Zeinab Ebrahimi; Gustavo Batista; Mohammad Deghat (Neurocomputing, 2025)

FastFlow: Early Yet Robust Network Flow Classification using the Minimal Number of Time-Series Packets. - Rushi Jayeshkumar Babaria; Minzhao Lyu; Gustavo Batista; Vijay Sivaraman (Proc. ACM Meas. Anal. Comput. Syst., 2025)

Nosy Layers, Noisy Fixes: Tackling DRAs in Federated Learning Systems using Explainable AI. - Meghali Nandi; Arash Shaghaghi; Nazatul Haque Sultan; Gustavo Batista; Raymond K. Zhao; Sanjay K. Jha (CoRR, 2025)

Instance-Wise Monotonic Calibration by Constrained Transformation. - Yunrui Zhang; Gustavo Batista; Salil S. Kanhere (CoRR, 2025)