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ORCIDEstevam Hruschka
Estevam R. Hruschka Jr. – Estevam Rafael Hruschka – Estevam Rafael Hruschka Junior
Person information
- affiliation: Megagon Labs
- affiliation: Carnegie Mellon University, Pittsburgh, USA
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2020 – today
- 2024
[c78]Aditi Mishra, Sajjadur Rahman, Kushan Mitra, Hannah Kim, Estevam Hruschka:
Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks. ACL (Findings) 2024: 8117-8139- [c77]Yunshu Wu, Hayate Iso, Pouya Pezeshkpour, Nikita Bhutani, Estevam Hruschka:
Less is More for Long Document Summary Evaluation by LLMs. EACL (2) 2024: 330-343 - [c76]Pouya Pezeshkpour, Estevam Hruschka:
Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions. NAACL-HLT (Findings) 2024: 2006-2017 - [i16]Pouya Pezeshkpour, Eser Kandogan, Nikita Bhutani, Sajjadur Rahman, Tom M. Mitchell, Estevam Hruschka:
Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions. CoRR abs/2402.01108 (2024) - [i15]Sajjadur Rahman, Frederick Choi, Hannah Kim, Dan Zhang, Estevam Hruschka:
Knowledge Acquisition and Integration with Expert-in-the-loop. CoRR abs/2402.03291 (2024) - [i14]Pouya Pezeshkpour, Estevam Hruschka:
Multi-Conditional Ranking with Large Language Models. CoRR abs/2404.00211 (2024) - [i13]Eser Kandogan, Sajjadur Rahman, Nikita Bhutani, Dan Zhang, Rafael Li Chen, Kushan Mitra, Sairam Gurajada, Pouya Pezeshkpour, Hayate Iso, Yanlin Feng, Hannah Kim, Chen Shen, Jin Wang, Estevam Hruschka:
A Blueprint Architecture of Compound AI Systems for Enterprise. CoRR abs/2406.00584 (2024) - 2023
- [c75]Bosung Kim, Hayate Iso, Nikita Bhutani, Estevam Hruschka, Ndapa Nakashole, Tom M. Mitchell:
Zero-shot Triplet Extraction by Template Infilling. IJCNLP (1) 2023: 272-284 - [c74]Nahyun Kwon
, Hannah Kim, Sajjadur Rahman, Dan Zhang, Estevam Hruschka:
Weedle: Composable Dashboard for Data-Centric NLP in Computational Notebooks. WWW (Companion Volume) 2023: 132-135 - [c73]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [i12]Dan Zhang, Hannah Kim, Rafael Li Chen, Eser Kandogan, Estevam Hruschka:
MEGAnno: Exploratory Labeling for NLP in Computational Notebooks. CoRR abs/2301.03095 (2023) - [i11]Sajjadur Rahman, Hannah Kim, Dan Zhang, Estevam Hruschka, Eser Kandogan:
Towards Multifaceted Human-Centered AI. CoRR abs/2301.03656 (2023) - [i10]Pouya Pezeshkpour, Estevam Hruschka:
Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions. CoRR abs/2308.11483 (2023) - [i9]Vishwas Mruthyunjaya, Pouya Pezeshkpour, Estevam Hruschka, Nikita Bhutani:
Rethinking Language Models as Symbolic Knowledge Graphs. CoRR abs/2308.13676 (2023) - [i8]Yunshu Wu, Hayate Iso, Pouya Pezeshkpour, Nikita Bhutani, Estevam Hruschka:
Less is More for Long Document Summary Evaluation by LLMs. CoRR abs/2309.07382 (2023) - [i7]Aditi Mishra, Sajjadur Rahman, Hannah Kim, Kushan Mitra, Estevam Hruschka:
Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks. CoRR abs/2311.05085 (2023) - [i6]Pouya Pezeshkpour, Hayate Iso, Thom Lake, Nikita Bhutani, Estevam Hruschka:
Distilling Large Language Models using Skill-Occupation Graph Context for HR-Related Tasks. CoRR abs/2311.06383 (2023) - [i5]Nedelina Teneva, Estevam Hruschka:
Knowledge Graphs are not Created Equal: Exploring the Properties and Structure of Real KGs. CoRR abs/2311.06414 (2023) - 2022
- [c72]Seiji Maekawa, Dan Zhang, Hannah Kim, Sajjadur Rahman, Estevam Hruschka:
Low-resource Interactive Active Labeling for Fine-tuning Language Models. EMNLP (Findings) 2022: 3230-3242 - [c71]Yutong Shao, Nikita Bhutani, Sajjadur Rahman, Estevam Hruschka:
Low-resource Entity Set Expansion: A Comprehensive Study on User-generated Text. NAACL-HLT (Findings) 2022: 1343-1353 - [i4]Bosung Kim, Hayate Iso, Nikita Bhutani, Estevam Hruschka, Ndapa Nakashole:
Zero-shot Triplet Extraction by Template Infilling. CoRR abs/2212.10708 (2022) - 2021
- [c70]Laurence Rodrigues do Amaral, Alexandre Henrick da Silva Alves, Raphael de Lima Mendes, Matheus de Souza Gomes, Pedro Luiz Lima Bertarini, Estevam Rafael Hruschka:
Applying Never-Ending Learning (NEL) Principles to Build a Gene Ontology (GO) Biocurator. CEC 2021: 458-465 - [c69]Estevam Hruschka, Tom M. Mitchell, Marko Grobelnik, Behzad Golshan:
WIT: Workshop on deriving Insights from user-generated Text. KDD 2021: 4131-4132 - [c68]Dongjin Choi, Sara Evensen, Çagatay Demiralp, Estevam Hruschka:
TagRuler: Interactive Tool for Span-Level Data Programming by Demonstration. WWW (Companion Volume) 2021: 673-677 - [i3]Dongjin Choi, Sara Evensen, Çagatay Demiralp, Estevam Hruschka:
TagRuler: Interactive Tool for Span-Level Data Programming by Demonstration. CoRR abs/2106.12767 (2021) - 2020
- [c67]Estevam R. Hruschka Jr.:
Data-Driven Never-Ending Learning Question Answering Systems. KDD 2020: 3579-3580
2010 – 2019
- 2019
- [c66]Edimilson Batista dos Santos, Igor Henrique P. Rodrigues, Estevam R. Hruschka Jr., Lucas Rezende Bruno:
Bayesian Networks for Inference and Discovery of Semantic Relations in a Never-Ending Learning System. BRACIS 2019: 687-692 - [c65]Saulo D. de S. Pedro, Estevam R. Hruschka Jr.:
Crowd-Powered Systems to Diminish the Effects of Semantic Drift. HAIS 2019: 697-709 - [i2]Daniel Severo, Flávio Amaro, Estevam R. Hruschka Jr., André Soares de Moura Costa:
Ward2ICU: A Vital Signs Dataset of Inpatients from the General Ward. CoRR abs/1910.00752 (2019) - 2018
- [j25]Tom M. Mitchell, William W. Cohen, Estevam R. Hruschka Jr., Partha P. Talukdar, Bo Yang, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matt Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapandula Nakashole, Emmanouil A. Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard C. Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, Joel Welling:
Never-ending learning. Commun. ACM 61(5): 103-115 (2018) - [j24]Felipe Quécole, Maísa Cristina Duarte, Estevam Rafael Hruschka Junior:
Coupling for Coreference Resolution in a Never-ending Learning System. J. Inf. Data Manag. 9(2): 124-134 (2018) - [c64]Rafael Garcia Leonel Miani, Estevam Rafael Hruschka Junior:
Eliminating Redundant and Irrelevant Association Rules in Large Knowledge Bases. ICEIS (1) 2018: 17-28 - [c63]José M. Giménez-García, Maísa Cristina Duarte, Antoine Zimmermann, Christophe Gravier, Estevam R. Hruschka Jr., Pierre Maret:
NELL2RDF: Reading the Web, Tracking the Provenance, and Publishing it as Linked Data. CKGSemStats@ISWC 2018 - [i1]José M. Giménez-García, Maisa C. Duarte, Antoine Zimmermann, Christophe Gravier, Estevam R. Hruschka Jr., Pierre Maret:
NELL2RDF: Reading the Web, and Publishing it as Linked Data. CoRR abs/1804.05639 (2018) - 2017
- [c62]Rafael Garcia Leonel Miani, Estevam Rafael Hruschka Junior:
Correcting Inconsistencies through Association Rules in Temporal Large Growing Knowledge Bases. BRACIS 2017: 1-6 - [c61]Rafael Garcia, Leonel Miani, Estevam Rafael Hruschka Junior:
Specific temporal association rules and temporal correlations to enlarge and detect inconsistencies in a large growing knowledge base. ICNC-FSKD 2017: 1565-1574 - [c60]Jerónimo Hernández-González, Estevam R. Hruschka Jr., Tom M. Mitchell:
Merging knowledge bases in different languages. TextGraphs@ACL 2017: 21-29 - 2016
- [j23]Stefano V. Albrecht, Bruno Bouchard, John S. Brownstein, David L. Buckeridge, Cornelia Caragea, Kevin M. Carter, Adnan Darwiche, Blaz Fortuna, Yannick Francillette, Sébastien Gaboury, C. Lee Giles, Marko Grobelnik, Estevam R. Hruschka Jr., Jeffrey O. Kephart, Parisa Kordjamshidi, Viliam Lisý, Daniele Magazzeni, João Marques-Silva, Pierre Marquis, David R. Martinez, Marek P. Michalowski, Arash Shaban-Nejad, Zeinab Noorian, Enrico Pontelli, Alex Rogers, Stephanie Rosenthal, Dan Roth, Arunesh Sinha, William W. Streilein, Sylvie Thiébaux, Tran Cao Son, Byron C. Wallace, Toby Walsh, Michael Witbrock, Jie Zhang:
Reports of the 2016 AAAI Workshop Program. AI Mag. 37(3): 99-108 (2016) - [j22]Nádia Félix Felipe da Silva, Luiz F. S. Coletta, Eduardo R. Hruschka, Estevam R. Hruschka Jr.:
Using unsupervised information to improve semi-supervised tweet sentiment classification. Inf. Sci. 355-356: 348-365 (2016) - [c59]Lucas Fonseca Navarro, Estevam R. Hruschka Jr., Ana Paula Appel:
Finding Inference Rules Using Graph Mining in Ontological Knowledge Bases. BRACIS 2016: 349-354 - [c58]Edimilson Batista dos Santos, Massilon Lourenço Fernandes, Estevam R. Hruschka Jr., Maísa Cristina Duarte:
Bayesian Networks for Identifying Semantic Relations in a Never-Ending Learning System. ISDA 2016: 279-288 - [c57]Wesley Willy Oliveira de Souza, Estevam Rafael Hruschka Junior:
Cognitive Conversation Language - CCL. ISDA 2016: 309-318 - [c56]Zhiyuan Chen, Estevam R. Hruschka Jr., Bing Liu:
Lifelong Machine Learning and Computer Reading the Web. KDD 2016: 2117-2118 - [c55]Lucas Fonseca Navarro, Estevam Rafael Hruschka Junior, Ana Paula Appel:
Ontological Networks: Mapping Ontological Knowledge Bases into Graphs. WWW (Companion Volume) 2016: 949-954 - [e1]Blaz Fortuna, Marko Grobelnik, Estevam R. Hruschka Jr., Michael Witbrock:
Knowledge Extraction from Text, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 12, 2016. AAAI Technical Report WS-16-10, AAAI Press 2016 [contents] - 2015
- [j21]Dunja Mladenic, Estevam R. Hruschka Jr., Marko Grobelnik:
Editorial. J. Web Semant. 35: 63 (2015) - [c54]Tom M. Mitchell, William W. Cohen, Estevam R. Hruschka Jr., Partha Pratim Talukdar, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matthew Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapandula Nakashole, Emmanouil A. Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard C. Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, Joel Welling:
Never-Ending Learning. AAAI 2015: 2302-2310 - 2014
- [j20]Nádia Félix F. da Silva, Eduardo R. Hruschka, Estevam R. Hruschka Jr.:
Tweet sentiment analysis with classifier ensembles. Decis. Support Syst. 66: 170-179 (2014) - [j19]Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti, Nelson F. F. Ebecken:
The influences of canonical evolutionary algorithm operators and variable orderings in learning Bayesian classifiers from data. Int. J. Hybrid Intell. Syst. 11(3): 183-195 (2014) - [j18]Laurence Rodrigues do Amaral, Estevam R. Hruschka Jr.:
Transgenic: An evolutionary algorithm operator. Neurocomputing 127: 104-113 (2014) - [c53]Luiz Fernando Sommaggio Coletta, Nádia Félix F. da Silva, Eduardo R. Hruschka, Estevam R. Hruschka Jr.:
Combining Classification and Clustering for Tweet Sentiment Analysis. BRACIS 2014: 210-215 - [c52]Rafael Garcia Leonel Miani, Estevam Rafael Hruschka Junior:
Analyzing the use of obvious and generalized association rules in a large knowledge base. HIS 2014: 1-6 - [c51]Paulo Henrique Barchi, Estevam Rafael Hruschka Junior:
Never-ending ontology extension through machine reading. HIS 2014: 266-272 - [c50]Maisa C. Duarte, Estevam R. Hruschka Jr.:
Exploring two views of coreference resolution in a never-ending learning system. HIS 2014: 273-278 - [c49]Maisa C. Duarte, Estevam R. Hruschka Jr.:
How to read the web in portuguese using the never-ending language learner's principles. ISDA 2014: 162-167 - [c48]Nádia Félix F. da Silva, Estevam R. Hruschka Jr., Eduardo R. Hruschka:
Biocom_Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble. SemEval@COLING 2014: 123-128 - 2013
- [j17]Lilian Anne Krug, Douglas Francisco Marcolino Gherardi, José Stech, Zelinda Margarida Andrade Nery Leão, Ruy Kenji Papa Kikuchi, Estevam Rafael Hruschka Junior, David John Suggett:
The construction of causal networks to estimate coral bleaching intensity. Environ. Model. Softw. 42: 157-167 (2013) - [j16]Estevam R. Hruschka Jr., Maisa C. Duarte, Maria C. Nicoletti:
Coupling as Strategy for Reducing Concept-Drift in Never-ending Learning Environments. Fundam. Informaticae 124(1-2): 47-61 (2013) - [j15]Maria C. Nicoletti, Flávia O. Santos de Sá Lisboa, Estevam R. Hruschka Jr.:
Automatic Learning of Temporal Relations Under the Closed World Assumption. Fundam. Informaticae 124(1-2): 133-151 (2013) - [c47]Lucas Fonseca Navarro, Ana Paula Appel, Estevam Rafael Hruschka Junior:
GraphDB - Storing Large Graphs on Secondary Memory. ADBIS (2) 2013: 177-186 - [c46]Reginaldo Aparecido Gotardo, Estevam Rafael Hruschka Junior, Sérgio Donizetti Zorzo:
Approach to Cold-Start Problem in Recommender Systems in the Context of Web-Based Education. ICMLA (2) 2013: 543-548 - [c45]Saulo D. de S. Pedro, Ana Paula Appel, Estevam R. Hruschka Jr.:
Autonomously reviewing and validating the knowledge base of a never-ending learning system. WWW (Companion Volume) 2013: 1195-1204 - 2012
- [c44]Laurence Rodrigues do Amaral, Estevam Rafael Hruschka Junior:
Never-ending learning principles in gene ontology classification using genetic algorithms. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c43]Vinicius Oliverio, Estevam R. Hruschka Jr.:
Contradiction Detection and Ontology Extension in a Never-Ending Learning System. IBERAMIA 2012: 1-10 - [c42]Saulo D. de S. Pedro, Estevam R. Hruschka Jr.:
Conversing Learning: Active Learning and Active Social Interaction for Human Supervision in Never-Ending Learning Systems. IBERAMIA 2012: 231-240 - [c41]Maria C. Nicoletti, Flávia O. Santos de Sá Lisboa, Estevam R. Hruschka Jr., Osvaldo Luiz De Oliveira:
Representation and automatic learning of temporal relations between time periods with uncertain boundaries. ISDA 2012: 443-448 - [c40]Saurabh Verma, Estevam R. Hruschka Jr.:
Coupled Bayesian Sets Algorithm for Semi-supervised Learning and Information Extraction. ECML/PKDD (2) 2012: 307-322 - [c39]Saulo D. de S. Pedro, Estevam R. Hruschka Jr.:
Collective intelligence as a source for machine learning self-supervision. WI&C 2012: 5 - 2011
- [j14]Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken:
Bayesian network classifiers: Beyond classification accuracy. Intell. Data Anal. 15(3): 279-298 (2011) - [j13]Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken:
A Bayesian imputation method for a clustering genetic algorithm. J. Comput. Methods Sci. Eng. 11(4): 173-183 (2011) - [j12]Ana Paula Appel, Estevam Rafael Hruschka Junior:
Centaurs - a Component Based Framework to Mine Large Graphs. J. Inf. Data Manag. 2(1): 19-26 (2011) - [c38]Laurence Rodrigues do Amaral, Estevam R. Hruschka Jr.:
Transgenic, an operator for evolutionary algorithms. IEEE Congress on Evolutionary Computation 2011: 1308-1314 - [c37]Thahir Mohamed, Estevam R. Hruschka Jr., Tom M. Mitchell:
Discovering Relations between Noun Categories. EMNLP 2011: 1447-1455 - [c36]Ana Paula Appel, Estevam Rafael Hruschka Junior:
Prophet - A Link-Predictor to Learn New Rules on NELL. ICDM Workshops 2011: 917-924 - [c35]Edimilson Batista dos Santos, Nelson F. F. Ebecken, Estevam R. Hruschka Jr.:
Learning Bayesian Network structures using Multiple Offspring Sampling. ISDA 2011: 362-367 - [c34]Maísa Cristina Duarte, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti:
Minimização do Impacto do Problema de Desvio de Conceito por Meio de Acoplamento em Ambiente de Aprendizado Sem Fim (Minimizing the Impact of the Concept Drift Problem by Using a Framework of Endless Learning) [in Portuguese]. STIL 2011 - 2010
- [c33]Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam R. Hruschka Jr., Tom M. Mitchell:
Toward an Architecture for Never-Ending Language Learning. AAAI 2010: 1306-1313 - [c32]Laurence Rodrigues do Amaral, Estevam R. Hruschka Jr.:
Gene ontology classification: Building high-level knowledge using genetic algorithms. IEEE Congress on Evolutionary Computation 2010: 1-7 - [c31]Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken:
A Distance-Based Mutation Operator for learning Bayesian Network structures using Evolutionary Algorithms. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c30]Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
Evolutionary Algorithm Using Random Multi-point Crossover Operator for Learning Bayesian Network Structures. ICMLA 2010: 430-435 - [c29]I-Hsien Yin, Estevam R. Hruschka Jr., Heloisa de Arruda Camargo:
Intelligent Classification System Using a Pruned Bayes Fuzzy Rule Set. ICMLA 2010: 635-640 - [c28]Ana Paula Appel, Estevam R. Hruschka Jr.:
Centaurs - A Component-based Framework to Mine Large Graphs. SBBD (Posters) 2010: 1:1-1:8 - [c27]Andrew Carlson, Justin Betteridge, Richard C. Wang, Estevam R. Hruschka Jr., Tom M. Mitchell:
Coupled semi-supervised learning for information extraction. WSDM 2010: 101-110
2000 – 2009
- 2009
- [j11]Gláucia M. Bressan, Vilma A. de Oliveira, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti:
Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop. Eng. Appl. Artif. Intell. 22(4-5): 579-592 (2009) - [j10]Eduardo R. Hruschka, Antonio J. T. Garcia, Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
On the influence of imputation in classification: practical issues. J. Exp. Theor. Artif. Intell. 21(1): 43-58 (2009) - [c26]Justin Betteridge, Andrew Carlson, Sue Ann Hong, Estevam R. Hruschka Jr., Edith L. M. Law, Tom M. Mitchell, Sophie H. Wang:
Toward Never Ending Language Learning. AAAI Spring Symposium: Learning by Reading and Learning to Read 2009: 1-2 - [c25]I-Hsien Yin, Estevam R. Hruschka Jr., Heloisa de Arruda Camargo:
The Impact of Pruning BayesFuzzy Rule Set. ISDA 2009: 456-461 - [c24]Tom M. Mitchell, Justin Betteridge, Andrew Carlson, Estevam R. Hruschka Jr., Richard C. Wang:
Populating the Semantic Web by Macro-reading Internet Text. ISWC 2009: 998-1002 - 2008
- [j9]Estevam R. Hruschka Jr., Maria do Carmo Nicoletti, Vilma A. de Oliveira, Gláucia M. Bressan:
BayesRule: A Markov-Blanket based procedure for extracting a set of probabilistic rules from Bayesian classifiers. Int. J. Hybrid Intell. Syst. 5(2): 83-96 (2008) - [j8]Marcos Evandro Cintra, Heloisa de Arruda Camargo, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti:
Automatic Construction of Fuzzy Rule Bases: a further Investigation into two Alternative Inductive Approaches. J. Univers. Comput. Sci. 14(15): 2456-2470 (2008) - 2007
- [j7]Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
Towards efficient variables ordering for Bayesian networks classifier. Data Knowl. Eng. 63(2): 258-269 (2007) - [j6]Estevam R. Hruschka Jr., Sebastian D. C. de O. Galvão:
Fast Conditional Independence-based Bayesian Classifier. J. Comput. Sci. Eng. 1(2): 162-176 (2007) - [j5]Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken:
Bayesian networks for imputation in classification problems. J. Intell. Inf. Syst. 29(3): 231-252 (2007) - [j4]Maria do Carmo Nicoletti, Lucas Baggio Figueira, Estevam R. Hruschka Jr.:
Transferring neural network based knowledge into an exemplar-based learner. Neural Comput. Appl. 16(3): 257-265 (2007) - [c23]Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti:
Conditional independence based learning of bayesian classifiers guided by a variable ordering genetic search. IEEE Congress on Evolutionary Computation 2007: 1444-1449 - [c22]Sebastian D. C. de O. Galvão, Estevam R. Hruschka Jr.:
A Markov Blanket Based Strategy to Optimize the Induction of Bayesian Classifiers When Using Conditional Independence Learning Algorithms. DaWaK 2007: 355-364 - [c21]Diego P. Vivencio, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti, Edimilson Batista dos Santos, Sebastian D. C. de O. Galvão:
Feature-weighted k-Nearest Neighbor Classifier. FOCI 2007: 481-486 - [c20]Estevam R. Hruschka Jr., Heloisa de Arruda Camargo, Marcos Evandro Cintra, Maria do Carmo Nicoletti:
BayesFuzzy: Using a Bayesian Classifier to Induce a Fuzzy Rule Base. FUZZ-IEEE 2007: 1-6 - [c19]Estevam R. Hruschka Jr., Maria do Carmo Nicoletti, Vilma A. de Oliveira, Gláucia M. Bressan:
Markov-Blanket Based Strategy for Translating a Bayesian Classifier into a Reduced Set of Classification Rules. HIS 2007: 192-197 - [c18]Estevam R. Hruschka Jr., Edimilson Batista dos Santos, Sebastian D. C. de O. Galvão:
Variable Ordering in the Conditional Independence Bayesian Classifier Induction Process: An Evolutionary Approach. HIS 2007: 204-209 - [c17]Gláucia M. Bressan, Vilma A. de Oliveira, Estevam R. Hruschka Jr., Maria C. Nicoletti:
Biomass Based Weed-Crop Competitiveness Classification Using Bayesian Networks. ISDA 2007: 121-126 - [c16]Saul D. de S. S. Pedro, Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
WNB: A Weighted Naïve Bayesian Classifier. ISDA 2007: 138-142 - [c15]Marcos Evandro Cintra, Heloisa de Arruda Camargo, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti:
Fuzzy Rule Base Generation through Genetic Algorithms and Bayesian Classifiers A Comparative Approach. ISDA 2007: 315-322 - [c14]Daniel Monegatto Santoro, Maria do Carmo Nicoletti, Estevam R. Hruschka Jr.:
C-Focus-3: a C-Focus with a New Heuristic Search Strategy. ISDA 2007: 479-484 - 2006
- [j3]Eduardo R. Hruschka, Estevam R. Hruschka Jr., Thiago F. Covoes, Nelson F. F. Ebecken:
Bayesian Feature Selection for Clustering Problems. J. Inf. Knowl. Manag. 5(4): 315-327 (2006) - [c13]João Roberto Bertini Jr., Maria do Carmo Nicoletti, Estevam R. Hruschka Jr., Arthur Ramer:
Two Variants of the Constructive Neural Network Tiling Algorithm. HIS 2006: 49 - [c12]Edimilson Batista dos Santos, Estevam R. Hruschka Jr.:
VOGA: Variable Ordering Genetic Algorithm for Learning Bayesian Classifiers. HIS 2006: 56 - [c11]João Roberto Bertini Jr., Maria do Carmo Nicoletti, Estevam R. Hruschka Jr.:
A Comparative Evaluation of Constructive Neural Networks Methods using PRM and BCP as TLU Training Algorithms. SMC 2006: 3497-3502 - 2005
- [c10]Maria do Carmo Nicoletti, Lucas Baggio Figueira, Estevam R. Hruschka Jr.:
Initializing an Exemplar Based Learning Process from a RuleNet Network. HIS 2005: 125-130 - [c9]Eduardo R. Hruschka, Thiago F. Covoes, Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
Feature Selection for Clustering Problems: a Hybrid Algorithm that Iterates Between k-means and a Bayesian Filter. HIS 2005: 405-410 - [c8]Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
Missing Values Imputation for a Clustering Genetic Algorithm. ICNC (3) 2005: 245-254 - [c7]Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken:
Applying Bayesian Networks for Meteorological Data Mining. SGAI Conf. (Applications) 2005: 122-133 - [c6]Daniel Monegatto Santoro, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti:
Selecting feature subsets for inducing classifiers using a committee of heterogeneous methods. SMC 2005: 375-380 - 2004
- [c5]Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken:
Feature Selection by Bayesian Networks. Canadian AI 2004: 370-379 - [c4]Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
Towards Efficient Imputation by Nearest-Neighbors: A Clustering-Based Approach. Australian Conference on Artificial Intelligence 2004: 513-525 - 2003
- [j2]Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken:
A Feature Selection Bayesian Approach for Extracting Classification Rules with a Clustering Genetic Algorithm. Appl. Artif. Intell. 17(5-6): 489-506 (2003) - [c3]Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
Evaluating a Nearest-Neighbor Method to Substitute Continuous Missing Values. Australian Conference on Artificial Intelligence 2003: 723-734 - [c2]Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
A Nearest-Neighbor Method as a Data Preparation Tool for a Clustering Genetic Algorithm. SBBD 2003: 319-327 - 2002
- [j1]Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
Missing values prediction with K2. Intell. Data Anal. 6(6): 557-566 (2002) - [c1]Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken:
A Data Preparation Bayesian Approach for a Clustering Genetic Algorithm. HIS 2002: 453-461
Coauthor Index
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