default search action
Gustavo 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
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j26]Arman Pashamokhtari
, Gustavo Batista
Efficient IoT Traffic Inference: From Multi-view Classification to Progressive Monitoring. ACM Trans. Internet Things 5(1): 5:1-5:30 (2024) - [c79]Yuvin Perera, Gustavo Batista, Wen Hu, Salil S. Kanhere, Sanjay K. Jha:
SAfER: Simplified Auto-encoder for (Anomalous) Event Recognition. DCOSS-IoT 2024: 229-233 - [c78]Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra:
Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. ICRA 2024: 15068-15075 - [c77]Feiyu Li, Hassan Habibi Gharakheili, Gustavo Batista:
Quantification Over Time. ECML/PKDD (5) 2024: 282-299 - [c76]Shayan Azizi
Poster: Understanding and Managing Changes in IoT Device Behaviors for Reliable Network Traffic Inference. SIGCOMM (Posters and Demos) 2024: 25-27 - [i12]Zeinab Ebrahimi, Gustavo Batista, Mohammad Deghat:
AA-DLADMM: An Accelerated ADMM-based Framework for Training Deep Neural Networks. CoRR abs/2401.03619 (2024) - [i11]Uzma Maroof, Gustavo Batista, Arash Shaghaghi, Sanjay K. Jha:
Towards Detecting IoT Event Spoofing Attacks Using Time-Series Classification. CoRR abs/2407.19662 (2024) - [i10]Carlos A. Rivera Alvarez, Arash Shaghaghi, Gustavo Batista, Salil S. Kanhere:
Towards Weaknesses and Attack Patterns Prediction for IoT Devices. CoRR abs/2408.13172 (2024) - 2023
- [j25]Arman Pashamokhtari
Dynamic Inference From IoT Traffic Flows Under Concept Drifts in Residential ISP Networks. IEEE Internet Things J. 10(17): 15761-15773 (2023) - [c75]Adriane Beatriz de Souza Serapião
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 - [i9]Arman Pashamokhtari, Norihiro Okui
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
- [j24]Antonio Rafael Sabino Parmezan
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
Hierarchical classification of pollinating flying insects under changing environments. Ecol. Informatics 70: 101751 (2022) - [c73]Tiago Pinho da Silva
Geographic Context-Based Stacking Learning for Election Prediction from Socio-economic Data. BRACIS (1) 2022: 641-656 - [c72]Bo Chen, Ali Bakhshi
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 - [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
- [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
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) - [c70]Waqar Hassan, André Gustavo Maletzke, Gustavo Batista:
Pitfalls in Quantification Assessment. CIKM Workshops 2021 - [c69]Aryan Sharma, Junye Li
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
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 - [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
- [j19]Vinícius M. A. de Souza
Challenges in benchmarking stream learning algorithms with real-world data. Data Min. Knowl. Discov. 34(6): 1805-1858 (2020) - [c66]Waqar Hassan
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
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 - [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)
2010 – 2019
- 2019
- [j18]Antonio Rafael Sabino Parmezan
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
Fast Similarity Matrix Profile for Music Analysis and Exploration. IEEE Trans. Multim. 21(1): 29-38 (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
EmbML Tool: Supporting the use of Supervised Learning Algorithms in Low-Cost Embedded Systems. ICTAI 2019: 1633-1637 - 2018
- [j16]Diego Furtado Silva
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) - [c59]Vinicius Souza
Evaluating Stream Classifiers with Delayed Labels Information. BRACIS 2018: 408-413 - [c58]Tiago Pinho da Silva
A Fuzzy Classifier for Data Streams with Infinitely Delayed Labels. CIARP 2018: 287-295 - [c57]Antonio Rafael Sabino Parmezan
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
- [j14]Vinícius Mourão Alves de Souza
Unsupervised active learning techniques for labeling training sets: An experimental evaluation on sequential data. Intell. Data Anal. 21(5): 1061-1095 (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
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
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
- [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
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
Class imbalance revisited: a new experimental setup to assess the performance of treatment methods. Knowl. Inf. Syst. 45(1): 247-270 (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
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
Classification of Evolving Data Streams with Infinitely Delayed Labels. ICMLA 2015: 214-219 - [c41]Rafael Giusti
Time Series Classification with Representation Ensembles. IDA 2015: 108-119 - [c40]Yu Qi, Goktug T. Cinar
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
An experimental analysis on time series transductive classification on graphs. IJCNN 2015: 1-8 - [c38]Vinícius M. A. de Souza
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
Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency. SDM 2015: 873-881 - 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) - [c35]Cristiano Inácio Lemes
Adding Diversity to Rank Examples in Anytime Nearest Neighbor Classification. ICMLA 2014: 129-134 - [c34]Vinícius M. A. de Souza
Extracting Texture Features for Time Series Classification. ICPR 2014: 1425-1430 - [c33]Celso André R. de Sousa, Vinícius M. A. de Souza
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 - [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) - 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) - [c31]Vinícius M. A. de Souza
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
Time Series Classification Using Compression Distance of Recurrence Plots. ICDM 2013: 687-696 - [c28]Diego Furtado Silva
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
Influence of Graph Construction on Semi-supervised Learning. ECML/PKDD (3) 2013: 160-175 - 2012
- [j7]Ronaldo C. Prati
A Complexity-Invariant Measure Based on Fractal Dimension for Time Series Classification. Int. J. Nat. Comput. Res. 3(3): 59-73 (2012) - [c24]Diego Furtado Silva, Vinícius M. A. de Souza
Spoken Digit Recognition in Portuguese Using Line Spectral Frequencies. IBERAMIA 2012: 241-250 - [c23]Gustavo Enrique De Almeida Prado Alves Batista, Diego Furtado Silva
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
- [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
A Survey on Graphical Methods for Classification Predictive Performance Evaluation. IEEE Trans. Knowl. Data Eng. 23(11): 1601-1618 (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
- [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) - [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
Classification of Live Moths Combining Texture, Color and Shape Primitives. ICMLA 2010: 903-906
2000 – 2009
- 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
Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules. HIS 2008: 537-542 - [c13]Ronaldo C. Prati
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 - 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) - 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
- [j2]Gustavo E. A. P. A. Batista, Ronaldo C. Prati
A study of the behavior of several methods for balancing machine learning training data. SIGKDD Explor. 6(1): 20-29 (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
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
- [b1]Gustavo Enrique De Almeida Prado Alves Batista:
Data pre-processing for supervised machine learning. University of São Paulo, Brazil, 2003 - [j1]Gustavo E. A. P. A. Batista
An Analysis of Four Missing Data Treatment Methods for Supervised Learning. Appl. Artif. Intell. 17(5-6): 519-533 (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
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
Applying One-Sided Selection to Unbalanced Datasets. MICAI 2000: 315-325
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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:23 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: