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ORCIDGustavo Batista
Gustavo E. A. P. A. Batista – Gustavo Enrique De Almeida Prado Alves Batista
Person information
- affiliation: University of New South Wales, Sydney, Australia
- affiliation (former): University of Sao Paulo, Brazil
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Books and Theses
- 2003
[b1]Gustavo Enrique De Almeida Prado Alves Batista:
Data pre-processing for supervised machine learning. University of São Paulo, Brazil, 2003
Journal Articles
- 2024
- [j26]Arman Pashamokhtari
, Gustavo Batista, Hassan Habibi Gharakheili:
Efficient IoT Traffic Inference: From Multi-view Classification to Progressive Monitoring. ACM Trans. Internet Things 5(1): 5:1-5:30 (2024) - 2023
- [j25]Arman Pashamokhtari, Norihiro Okui, Masataka Nakahara, Ayumu Kubota, Gustavo Batista, Hassan Habibi Gharakheili:
Dynamic Inference From IoT Traffic Flows Under Concept Drifts in Residential ISP Networks. IEEE Internet Things J. 10(17): 15761-15773 (2023) - 2022
- [j24]Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Time Series Prediction via Similarity Search: Exploring Invariances, Distance Measures and Ensemble Functions. IEEE Access 10: 78022-78043 (2022) - [j23]Arman Pashamokhtari, Gustavo Batista, Hassan Habibi Gharakheili:
AdIoTack: Quantifying and refining resilience of decision tree ensemble inference models against adversarial volumetric attacks on IoT networks. Comput. Secur. 120: 102801 (2022) - [j22]Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Arpita Seth, Indre Zliobaite, Gustavo E. A. P. A. Batista:
Hierarchical classification of pollinating flying insects under changing environments. Ecol. Informatics 70: 101751 (2022) - 2021
- [j21]L. H. M. Jacintho, Tiago Pinho da Silva, Antonio Rafael Sabino Parmezan, Gustavo E. A. P. A. Batista:
Analysing Spatio-Temporal Voting Patterns in Brazilian Elections Through a Simple Data Science Pipeline. J. Inf. Data Manag. 12(1) (2021) - [j20]Junye Li, Aryan Sharma, Deepak Mishra, Gustavo Batista, Aruna Seneviratne:
COVID-Safe Spatial Occupancy Monitoring Using OFDM-Based Features and Passive WiFi Samples. ACM Trans. Manag. Inf. Syst. 12(4): 34:1-34:24 (2021) - 2020
- [j19]Vinícius M. A. de Souza, Denis Moreira dos Reis, André Gustavo Maletzke, Gustavo E. A. P. A. Batista:
Challenges in benchmarking stream learning algorithms with real-world data. Data Min. Knowl. Discov. 34(6): 1805-1858 (2020) - 2019
- [j18]Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
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. 484: 302-337 (2019) - [j17]Diego Furtado Silva, Chin-Chia Michael Yeh, Yan Zhu, Gustavo E. A. P. A. Batista, Eamonn J. Keogh:
Fast Similarity Matrix Profile for Music Analysis and Exploration. IEEE Trans. Multim. 21(1): 29-38 (2019) - 2018
- [j16]Diego Furtado Silva, Rafael Giusti, Eamonn J. Keogh, Gustavo E. A. P. A. Batista:
Speeding up similarity search under dynamic time warping by pruning unpromising alignments. Data Min. Knowl. Discov. 32(4): 988-1016 (2018) - [j15]André Gustavo Maletzke, Denis Moreira dos Reis, Gustavo E. A. P. A. Batista:
Combining instance selection and self-training to improve data stream quantification. J. Braz. Comput. Soc. 24(1): 12:1-12:17 (2018) - 2017
- [j14]Vinícius Mourão Alves de Souza, Rafael Geraldeli Rossi, Gustavo E. A. P. A. Batista, Solange O. Rezende:
Unsupervised active learning techniques for labeling training sets: An experimental evaluation on sequential data. Intell. Data Anal. 21(5): 1061-1095 (2017) - 2015
- [j13]Gustavo E. A. P. A. Batista, Myriam Regattieri Delgado, Flávia Cristina Bernardini:
ENIAC 2013 Special Issue. J. Intell. Robotic Syst. 80(Supplement-1): 225-226 (2015) - [j12]Diego Furtado Silva, Vinícius M. A. de Souza, Daniel P. W. Ellis, Eamonn J. Keogh, Gustavo E. A. P. A. Batista:
Exploring Low Cost Laser Sensors to Identify Flying Insect Species - Evaluation of Machine Learning and Signal Processing Methods. J. Intell. Robotic Syst. 80(Supplement-1): 313-330 (2015) - [j11]Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Diego Furtado Silva:
Class imbalance revisited: a new experimental setup to assess the performance of treatment methods. Knowl. Inf. Syst. 45(1): 247-270 (2015) - 2014
- [j10]Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Oben Moses Tataw, Vinícius M. A. de Souza:
CID: an efficient complexity-invariant distance for time series. Data Min. Knowl. Discov. 28(3): 634-669 (2014) - [j9]Rosa Del Gaudio, Gustavo E. A. P. A. Batista, António Branco:
Coping with highly imbalanced datasets: A case study with definition extraction in a multilingual setting. Nat. Lang. Eng. 20(3): 327-359 (2014) - 2013
- [j8]Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Gustavo E. A. P. A. Batista, M. Brandon Westover, Qiang Zhu, Jesin Zakaria, Eamonn J. Keogh:
Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping. ACM Trans. Knowl. Discov. Data 7(3): 10:1-10:31 (2013) - 2012
- [j7]Ronaldo C. Prati, Gustavo E. A. P. A. Batista:
A Complexity-Invariant Measure Based on Fractal Dimension for Time Series Classification. Int. J. Nat. Comput. Res. 3(3): 59-73 (2012) - 2011
- [j6]Claudia Regina Milaré, Gustavo E. A. P. A. Batista, André C. P. L. F. de Carvalho:
A hybrid approach to learn with imbalanced classes using evolutionary algorithms. Log. J. IGPL 19(2): 293-303 (2011) - [j5]Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard:
A Survey on Graphical Methods for Classification Predictive Performance Evaluation. IEEE Trans. Knowl. Data Eng. 23(11): 1601-1618 (2011) - 2010
- [j4]Claudia Regina Milaré, Gustavo E. A. P. A. Batista, André C. P. L. F. de Carvalho:
A Study of the Influence of Rule Measures in Classifiers Induced by Evolutionary Algorithms. IEEE Intell. Informatics Bull. 11(1): 8-13 (2010) - 2006
- [j3]Gustavo E. A. P. A. Batista, Claudia Regina Milaré, Ronaldo Cristiano Prati, Maria Carolina Monard:
A Comparison of Methods for Rule Subset Selection Applied to Associative Classification. Inteligencia Artif. 10(32): 29-35 (2006) - 2004
- [j2]Gustavo E. A. P. A. Batista, Ronaldo C. Prati, Maria Carolina Monard:
A study of the behavior of several methods for balancing machine learning training data. SIGKDD Explor. 6(1): 20-29 (2004) - 2003
- [j1]Gustavo E. A. P. A. Batista, Maria Carolina Monard:
An Analysis of Four Missing Data Treatment Methods for Supervised Learning. Appl. Artif. Intell. 17(5-6): 519-533 (2003)
Conference and Workshop Papers
- 2023
- [c75]Adriane B. S. Serapião, Zahra Donyavi, Gustavo Batista:
Ensembles of Classifiers and Quantifiers with Data Fusion for Quantification Learning. DS 2023: 3-17 - [c74]Zahra Donyavi, Adriane Serapio, Gustavo Batista:
MC-SQ: A Highly Accurate Ensemble for Multi-class Quantification. SDM 2023: 622-630 - 2022
- [c73]Tiago Pinho da Silva, Antonio Rafael Sabino Parmezan, Gustavo E. A. P. A. Batista:
Geographic Context-Based Stacking Learning for Election Prediction from Socio-economic Data. BRACIS (1) 2022: 641-656 - [c72]Bo Chen, Ali Bakhshi, Gustavo Batista, Brian Wai-Him Ng, Tat-Jun Chin:
Update Compression for Deep Neural Networks on the Edge. CVPR Workshops 2022: 3075-3085 - [c71]Daravichet Tin, Maryam Shahpasand, Hassan Habibi Gharakheili, Gustavo Batista:
Classifying Time-Series of IoT Flow Activity using Deep Learning and Intransitive Features. SKIMA 2022: 192-197 - 2021
- [c70]Waqar Hassan, André Gustavo Maletzke, Gustavo Batista:
Pitfalls in Quantification Assessment. CIKM Workshops 2021 - [c69]Aryan Sharma, Junye Li, Deepak Mishra, Gustavo Batista, Aruna Seneviratne:
Passive WiFi CSI Sensing Based Machine Learning Framework for COVID-Safe Occupancy Monitoring. ICC Workshops 2021: 1-6 - [c68]André Gustavo Maletzke, Denis Moreira dos Reis, Waqar Hassan, Gustavo Batista:
Accurately Quantifying under Score Variability. ICDM 2021: 1228-1233 - [c67]Tiago Pinho da Silva, Antonio Rafael Sabino Parmezan, Gustavo E. A. P. A. Batista:
A Graph-Based Spatial Cross-Validation Approach for Assessing Models Learned with Selected Features to Understand Election Results. ICMLA 2021: 909-915 - 2020
- [c66]Waqar Hassan, André Gustavo Maletzke, Gustavo E. A. P. A. Batista:
Accurately Quantifying a Billion Instances per Second. DSAA 2020: 1-10 - [c65]Jáder M. C. de Sá, André L. D. Rossi, Gustavo E. A. P. A. Batista, Luís Paulo F. Garcia:
Algorithm Recommendation for Data Streams. ICPR 2020: 6073-6080 - [c64]André Gustavo Maletzke, Waqar Hassan, Denis Moreira dos Reis, Gustavo E. A. P. A. Batista:
The Importance of the Test Set Size in Quantification Assessment. IJCAI 2020: 2640-2646 - [c63]Antonio Rafael Sabino Parmezan, Diego Furtado Silva, Gustavo E. A. P. A. Batista:
A Combination of Local Approaches for Hierarchical Music Genre Classification. ISMIR 2020: 740-747 - [c62]Gabriel A. F. Rebello, Yining Hu, Kanchana Thilakarathna, Gustavo Batista, Aruna Seneviratne, Otto Carlos Muniz Bandeira Duarte:
Melhorando a Acurácia da Detecção de Lavagem de Dinheiro na Rede Bitcoin. SBRC 2020: 728-741 - 2019
- [c61]André Gustavo Maletzke, Denis Moreira dos Reis, Everton Alvares Cherman, Gustavo E. A. P. A. Batista:
DyS: A Framework for Mixture Models in Quantification. AAAI 2019: 4552-4560 - [c60]Lucas Tsutsui da Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
EmbML Tool: Supporting the use of Supervised Learning Algorithms in Low-Cost Embedded Systems. ICTAI 2019: 1633-1637 - 2018
- [c59]Vinicius Souza, Tiago Pinho da Silva, Gustavo E. A. P. A. Batista:
Evaluating Stream Classifiers with Delayed Labels Information. BRACIS 2018: 408-413 - [c58]Tiago Pinho da Silva, Vinícius Mourão Alves de Souza, Gustavo Enrique De Almeida Prado Alves Batista, Heloisa de Arruda Camargo:
A Fuzzy Classifier for Data Streams with Infinitely Delayed Labels. CIARP 2018: 287-295 - [c57]Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Towards Hierarchical Classification of Data Streams. CIARP 2018: 314-322 - [c56]Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Elastic Time Series Motifs and Discords. ICMLA 2018: 237-242 - [c55]Denis Moreira dos Reis, André Gustavo Maletzke, Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Classifying and Counting with Recurrent Contexts. KDD 2018: 1983-1992 - [c54]André Gustavo Maletzke, Denis Moreira dos Reis, Everton Alvares Cherman, Gustavo E. A. P. A. Batista:
On the Need of Class Ratio Insensitive Drift Tests for Data Streams. LIDTA@ECML/PKDD 2018: 110-124 - [c53]Denis Moreira dos Reis, André Gustavo Maletzke, Everton Alvares Cherman, Gustavo Enrique De Almeida Prado Alves Batista:
One-Class Quantification. ECML/PKDD (1) 2018: 273-289 - [c52]Denis Moreira dos Reis, André Gustavo Maletzke, Gustavo E. A. P. A. Batista:
Unsupervised context switch for classification tasks on data streams with recurrent concepts. SAC 2018: 518-524 - 2017
- [c51]André Gustavo Maletzke, Denis Moreira dos Reis, Gustavo E. A. P. A. Batista:
Quantification in Data Streams: Initial Results. BRACIS 2017: 43-48 - 2016
- [c50]Diego Furtado Silva, Gustavo E. A. P. A. Batista, Eamonn J. Keogh:
Prefix and Suffix Invariant Dynamic Time Warping. ICDM 2016: 1209-1214 - [c49]Rafael Giusti, Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Improved Time Series Classification with Representation Diversity and SVM. ICMLA 2016: 1-6 - [c48]Celso André R. de Sousa, Gustavo E. A. P. A. Batista:
Constrained Local and Global Consistency for semi-supervised learning. ICPR 2016: 1689-1694 - [c47]Diego Furtado Silva, Chin-Chia Michael Yeh, Gustavo E. A. P. A. Batista, Eamonn J. Keogh:
SiMPle: Assessing Music Similarity Using Subsequences Joins. ISMIR 2016: 23-29 - [c46]Denis Moreira dos Reis, Peter A. Flach, Stan Matwin, Gustavo E. A. P. A. Batista:
Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test. KDD 2016: 1545-1554 - [c45]Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Speeding Up All-Pairwise Dynamic Time Warping Matrix Calculation. SDM 2016: 837-845 - 2015
- [c44]Luan Soares Oliveira, Gustavo E. A. P. A. Batista:
IGMM-CD: A Gaussian Mixture Classification Algorithm for Data Streams with Concept Drifts. BRACIS 2015: 55-61 - [c43]Antonio Rafael Sabino Parmezan, Gustavo E. A. P. A. Batista:
A Study of the Use of Complexity Measures in the Similarity Search Process Adopted by kNN Algorithm for Time Series Prediction. ICMLA 2015: 45-51 - [c42]Vinícius M. A. de Souza, Diego Furtado Silva, Gustavo E. A. P. A. Batista, João Gama:
Classification of Evolving Data Streams with Infinitely Delayed Labels. ICMLA 2015: 214-219 - [c41]Rafael Giusti, Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Time Series Classification with Representation Ensembles. IDA 2015: 108-119 - [c40]Yu Qi, Goktug T. Cinar, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Yueming Wang, José C. Príncipe:
Effective insect recognition using a stacked autoencoder with maximum correntropy criterion. IJCNN 2015: 1-7 - [c39]Celso André R. de Sousa, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
An experimental analysis on time series transductive classification on graphs. IJCNN 2015: 1-8 - [c38]Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Nilson E. Souza-Filho:
Automatic classification of drum sounds with indefinite pitch. IJCNN 2015: 1-8 - [c37]Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Music Shapelets for Fast Cover Song Recognition. ISMIR 2015: 441-447 - [c36]Vinícius M. A. de Souza, Diego Furtado Silva, João Gama, Gustavo E. A. P. A. Batista:
Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency. SDM 2015: 873-881 - 2014
- [c35]Cristiano Inácio Lemes, Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Adding Diversity to Rank Examples in Anytime Nearest Neighbor Classification. ICMLA 2014: 129-134 - [c34]Vinícius M. A. de Souza, Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Extracting Texture Features for Time Series Classification. ICPR 2014: 1425-1430 - [c33]Celso André R. de Sousa, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Time Series Transductive Classification on Imbalanced Data Sets: An Experimental Study. ICPR 2014: 3780-3785 - [c32]Diego Furtado Silva, Rafael Geraldeli Rossi, Solange Oliveira Rezende, Gustavo Enrique De Almeida Prado Alves Batista:
Music Classification by Transductive Learning Using Bipartite Heterogeneous Networks. ISMIR 2014: 113-118 - 2013
- [c31]Vinícius M. A. de Souza, Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Classification of Data Streams Applied to Insect Recognition: Initial Results. BRACIS 2013: 76-81 - [c30]Rafael Giusti, Gustavo E. A. P. A. Batista:
An Empirical Comparison of Dissimilarity Measures for Time Series Classification. BRACIS 2013: 82-88 - [c29]Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Time Series Classification Using Compression Distance of Recurrence Plots. ICDM 2013: 687-696 - [c28]Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Daniel P. W. Ellis:
Applying Machine Learning and Audio Analysis Techniques to Insect Recognition in Intelligent Traps. ICMLA (1) 2013: 99-104 - [c27]Diego Furtado Silva, Hélène Papadopoulos, Gustavo Enrique De Almeida Prado Alves Batista, Daniel P. W. Ellis:
A Video Compression-Based Approach to Measure Music Structural Similarity. ISMIR 2013: 95-100 - [c26]Yanping Chen, Bing Hu, Eamonn J. Keogh, Gustavo E. A. P. A. Batista:
DTW-D: time series semi-supervised learning from a single example. KDD 2013: 383-391 - [c25]Celso André R. de Sousa, Solange O. Rezende, Gustavo E. A. P. A. Batista:
Influence of Graph Construction on Semi-supervised Learning. ECML/PKDD (3) 2013: 160-175 - 2012
- [c24]Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Rafael Giusti:
Spoken Digit Recognition in Portuguese Using Line Spectral Frequencies. IBERAMIA 2012: 241-250 - [c23]Gustavo Enrique De Almeida Prado Alves Batista, Diego Furtado Silva, Ronaldo Cristiano Prati:
An Experimental Design to Evaluate Class Imbalance Treatment Methods. ICMLA (2) 2012: 95-101 - [c22]Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Gustavo E. A. P. A. Batista, M. Brandon Westover, Qiang Zhu, Jesin Zakaria, Eamonn J. Keogh:
Searching and mining trillions of time series subsequences under dynamic time warping. KDD 2012: 262-270 - [c21]Qiang Zhu, Gustavo E. A. P. A. Batista, Thanawin Rakthanmanon, Eamonn J. Keogh:
A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets. SDM 2012: 999-1010 - 2011
- [c20]Gustavo E. A. P. A. Batista, Yuan Hao, Eamonn J. Keogh, Agenor Mafra-Neto:
Towards Automatic Classification on Flying Insects Using Inexpensive Sensors. ICMLA (1) 2011: 364-369 - [c19]Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Agenor Mafra-Neto, Edgar Rowton:
SIGKDD demo: sensors and software to allow computational entomology, an emerging application of data mining. KDD 2011: 761-764 - [c18]Gustavo E. A. P. A. Batista, Xiaoyue Wang, Eamonn J. Keogh:
A Complexity-Invariant Distance Measure for Time Series. SDM 2011: 699-710 - 2010
- [c17]Rafael Giusti, Gustavo E. A. P. A. Batista:
Discovering Knowledge Rules with Multi-Objective Evolutionary Computing. ICMLA 2010: 119-124 - [c16]Gustavo E. A. P. A. Batista, Bilson J. L. Campana, Eamonn J. Keogh:
Classification of Live Moths Combining Texture, Color and Shape Primitives. ICMLA 2010: 903-906 - 2009
- [c15]Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard:
Data mining with imbalanced class distributions: concepts and methods. IICAI 2009: 359-376 - 2008
- [c14]Rafael Giusti, Gustavo E. A. P. A. Batista, Ronaldo Cristiano Prati:
Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules. HIS 2008: 537-542 - [c13]Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard:
A Study with Class Imbalance and Random Sampling for a Decision Tree Learning System. IFIP AI 2008: 131-140 - [c12]Edson Takashi Matsubara, Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard:
Missing Value Imputation Using a Semi-supervised Rank Aggregation Approach. SBIA 2008: 217-226 - 2005
- [c11]Gustavo E. A. P. A. Batista, Ronaldo C. Prati, Maria Carolina Monard:
Balancing Strategies and Class Overlapping. IDA 2005: 24-35 - [c10]Edson Takashi Matsubara, Maria Carolina Monard, Gustavo E. A. P. A. Batista:
Multi-view Semi-supervised Learning: An Approach to Obtain Different Views from Text Datasets. LAPTEC 2005: 97-104 - 2004
- [c9]Gustavo E. A. P. A. Batista, Maria Carolina Monard, Ana L. C. Bazzan:
Improving Rule Induction Precision for Automated Annotation by Balancing Skewed Data Sets. KELSI 2004: 20-32 - [c8]Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard:
Class Imbalances versus Class Overlapping: An Analysis of a Learning System Behavior. MICAI 2004: 312-321 - [c7]Claudia Regina Milaré, Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard:
Applying Genetic and Symbolic Learning Algorithms to Extract Rules from Artificial Neural Networks. MICAI 2004: 833-843 - [c6]Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard:
Learning with Class Skews and Small Disjuncts. SBIA 2004: 296-306 - 2003
- [c5]Gustavo E. A. P. A. Batista, Ana L. C. Bazzan, Maria Carolina Monard:
Balancing Training Data for Automated Annotation of Keywords: a Case Study. WOB 2003: 10-18 - 2002
- [c4]Gustavo E. A. P. A. Batista, Maria Carolina Monard:
A Study of K-Nearest Neighbour as an Imputation Method. HIS 2002: 251-260 - [c3]Ana Carolina Lorena, Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard:
The Influence of Noisy Patterns in the Performance of Learning Methods in the Splice Junction Recognition Problem. SBRN 2002: 31-37 - [c2]Ana Carolina Lorena, Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard:
Splice Junction Recognition using Machine Learning Techniques. WOB 2002: 32-39 - 2000
- [c1]Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard:
Applying One-Sided Selection to Unbalanced Datasets. MICAI 2000: 315-325
Informal and Other Publications
- 2024
- [i10]Zeinab Ebrahimi, Gustavo Batista, Mohammad Deghat:
AA-DLADMM: An Accelerated ADMM-based Framework for Training Deep Neural Networks. CoRR abs/2401.03619 (2024) - 2023
- [i9]Arman Pashamokhtari, Norihiro Okui, Masataka Nakahara, Ayumu Kubota, Gustavo Batista, Hassan Habibi Gharakheili:
Quantifying and Managing Impacts of Concept Drifts on IoT Traffic Inference in Residential ISP Networks. CoRR abs/2301.06695 (2023) - [i8]Ayyoob Hamza, Hassan Habibi Gharakheili, Theophilus A. Benson, Gustavo Batista, Vijay Sivaraman:
Detecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity. CoRR abs/2304.04987 (2023) - [i7]Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra:
Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. CoRR abs/2309.09021 (2023) - 2022
- [i6]Bo Chen, Ali Bakhshi, Gustavo Batista, Brian Wai-Him Ng, Tat-Jun Chin:
Update Compression for Deep Neural Networks on the Edge. CoRR abs/2203.04516 (2022) - [i5]Arman Pashamokhtari, Gustavo Batista, Hassan Habibi Gharakheili:
AdIoTack: Quantifying and Refining Resilience of Decision Tree Ensemble Inference Models against Adversarial Volumetric Attacks on IoT Networks. CoRR abs/2203.09792 (2022) - 2021
- [i4]Lucas Tsutsui da Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
An Open-Source Tool for Classification Models in Resource-Constrained Hardware. CoRR abs/2105.05983 (2021) - 2020
- [i3]Denis Moreira dos Reis, Marcílio de Souto, Elaine P. M. de Sousa, Gustavo E. A. P. A. Batista:
Quantifying With Only Positive Training Data. CoRR abs/2004.10356 (2020) - [i2]Vinícius M. A. de Souza, Denis Moreira dos Reis, André Gustavo Maletzke, Gustavo E. A. P. A. Batista:
Challenges in Benchmarking Stream Learning Algorithms with Real-world Data. CoRR abs/2005.00113 (2020) - 2014
- [i1]Yanping Chen, Adena Why, Gustavo E. A. P. A. Batista, Agenor Mafra-Neto, Eamonn J. Keogh:
Flying Insect Classification with Inexpensive Sensors. CoRR abs/1403.2654 (2014)
Coauthor Index
André C. P. L. F. de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
Ronaldo C. Prati
aka: Ronaldo Cristiano Prati
aka: Ronaldo Cristiano Prati
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Citation data
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load citations from opencitations.net
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OpenAlex data
Load additional information about publications from 
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last updated on 2024-04-25 02:21 CEST by the dblp team
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