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Parte de monografia/livro
Risks of semi-supervised learning: how unlabeled data can degrade performance of generative classifiers (2006)
Cozman, Fabio Gagliardi ; Cohen, Ira
Source: Semi-supervised learning. Unidade: EP
Subjects: APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL, ALGORITMOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COZMAN, Fabio Gagliardi e COHEN, Ira. Risks of semi-supervised learning: how unlabeled data can degrade performance of generative classifiers. Semi-supervised learning. Tradução . Cambridge: MIT Press, 2006. . Disponível em: https://repositorio.usp.br/directbitstream/df0ebf0c-1d85-4d79-9dd0-d1048287d165/Cozman-2006-risks%20of%20semi%20supervised%20learning.pdf. Acesso em: 05 nov. 2024.
APA
Cozman, F. G., & Cohen, I. (2006). Risks of semi-supervised learning: how unlabeled data can degrade performance of generative classifiers. In Semi-supervised learning. Cambridge: MIT Press. Recuperado de https://repositorio.usp.br/directbitstream/df0ebf0c-1d85-4d79-9dd0-d1048287d165/Cozman-2006-risks%20of%20semi%20supervised%20learning.pdf
NLM
Cozman FG, Cohen I. Risks of semi-supervised learning: how unlabeled data can degrade performance of generative classifiers [Internet]. In: Semi-supervised learning. Cambridge: MIT Press; 2006. [citado 2024 nov. 05 ] Available from: https://repositorio.usp.br/directbitstream/df0ebf0c-1d85-4d79-9dd0-d1048287d165/Cozman-2006-risks%20of%20semi%20supervised%20learning.pdf
Vancouver
Cozman FG, Cohen I. Risks of semi-supervised learning: how unlabeled data can degrade performance of generative classifiers [Internet]. In: Semi-supervised learning. Cambridge: MIT Press; 2006. [citado 2024 nov. 05 ] Available from: https://repositorio.usp.br/directbitstream/df0ebf0c-1d85-4d79-9dd0-d1048287d165/Cozman-2006-risks%20of%20semi%20supervised%20learning.pdf
Trabalho de evento
Splitting the unsupervised and supervised components of semi-supervised learning (2005)
Oliveira, Clayton Silva; Cozman, Fabio Gagliardi ; Cohen, Ira
Source: ICML : proceedings. Conference titles: Workshop Learning with Partially Classified Training Data. Unidade: EP
Subjects: APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Clayton Silva e COZMAN, Fabio Gagliardi e COHEN, Ira. Splitting the unsupervised and supervised components of semi-supervised learning. 2005, Anais.. Bonn: International Machine Learning Society, 2005. Disponível em: http://www.ijcai.org/papers/0841.pdf. Acesso em: 05 nov. 2024.
APA
Oliveira, C. S., Cozman, F. G., & Cohen, I. (2005). Splitting the unsupervised and supervised components of semi-supervised learning. In ICML : proceedings. Bonn: International Machine Learning Society. Recuperado de http://www.ijcai.org/papers/0841.pdf
NLM
Oliveira CS, Cozman FG, Cohen I. Splitting the unsupervised and supervised components of semi-supervised learning [Internet]. ICML : proceedings. 2005 ;[citado 2024 nov. 05 ] Available from: http://www.ijcai.org/papers/0841.pdf
Vancouver
Oliveira CS, Cozman FG, Cohen I. Splitting the unsupervised and supervised components of semi-supervised learning [Internet]. ICML : proceedings. 2005 ;[citado 2024 nov. 05 ] Available from: http://www.ijcai.org/papers/0841.pdf
Artigo de periodico
Learning probabilistic classifiers for human–computer interaction applications (2005)
Sebe, Nicu; Cohen, Ira; Cozman, Fabio Gagliardi ; Gevers, Theo; Huang, Thomas S.
Source: Multimedia Systems. Unidade: EP
Subjects: INTELIGÊNCIA ARTIFICIAL, INTERAÇÃO HOMEM-MÁQUINA, VISÃO COMPUTACIONAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SEBE, Nicu et al. Learning probabilistic classifiers for human–computer interaction applications. Multimedia Systems, p. 1-15, 2005Tradução . . Disponível em: https://doi.org/10.1007/s00530-005-0177-4. Acesso em: 05 nov. 2024.
APA
Sebe, N., Cohen, I., Cozman, F. G., Gevers, T., & Huang, T. S. (2005). Learning probabilistic classifiers for human–computer interaction applications. Multimedia Systems, 1-15. doi:10.1007/s00530-005-0177-4
NLM
Sebe N, Cohen I, Cozman FG, Gevers T, Huang TS. Learning probabilistic classifiers for human–computer interaction applications [Internet]. Multimedia Systems. 2005 ; 1-15.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00530-005-0177-4
Vancouver
Sebe N, Cohen I, Cozman FG, Gevers T, Huang TS. Learning probabilistic classifiers for human–computer interaction applications [Internet]. Multimedia Systems. 2005 ; 1-15.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/s00530-005-0177-4
Artigo de periodico
Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction (2004)
Cohen, Ira; Cozman, Fabio Gagliardi ; Sebe, Nicu; Cirelo, Marcelo Cesar; Huang, Thomas S.; Fellow
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence. Unidade: EP
Subjects: APRENDIZADO COMPUTACIONAL, INTERAÇÃO HOMEM-MÁQUINA, RECONHECIMENTO DE IMAGEM, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COHEN, Ira et al. Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction. IEEE Transactions on Pattern Analysis and Machine Intelligence, v. 26, n. 12, p. 1553-1567, 2004Tradução . . Disponível em: https://doi.org/10.1109/tpami.2004.127. Acesso em: 05 nov. 2024.
APA
Cohen, I., Cozman, F. G., Sebe, N., Cirelo, M. C., Huang, T. S., & Fellow,. (2004). Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26( 12), 1553-1567. doi:10.1109/tpami.2004.127
NLM
Cohen I, Cozman FG, Sebe N, Cirelo MC, Huang TS, Fellow. Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2004 ; 26( 12): 1553-1567.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1109/tpami.2004.127
Vancouver
Cohen I, Cozman FG, Sebe N, Cirelo MC, Huang TS, Fellow. Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2004 ; 26( 12): 1553-1567.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1109/tpami.2004.127
Trabalho de evento
Semi-supervised learning and model search (2003)
Cozman, Fabio Gagliardi ; Cohen, Ira; Cirelo, Marcelo Cesar
Source: ICML-2003 : proceedings.. Conference titles: International Conference on Machine Learning. Unidade: EP
Subjects: APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COZMAN, Fabio Gagliardi e COHEN, Ira e CIRELO, Marcelo Cesar. Semi-supervised learning and model search. 2003, Anais.. Menlo Park, CA: AAAI Press, 2003. Disponível em: https://repositorio.usp.br/directbitstream/d50342b6-ec81-4054-a7b6-c8e04caa3ed2/Cozman-2003-semi%20supervised%20learning%20and%20model%20search.pdf. Acesso em: 05 nov. 2024.
APA
Cozman, F. G., Cohen, I., & Cirelo, M. C. (2003). Semi-supervised learning and model search. In ICML-2003 : proceedings.. Menlo Park, CA: AAAI Press. Recuperado de https://repositorio.usp.br/directbitstream/d50342b6-ec81-4054-a7b6-c8e04caa3ed2/Cozman-2003-semi%20supervised%20learning%20and%20model%20search.pdf
NLM
Cozman FG, Cohen I, Cirelo MC. Semi-supervised learning and model search [Internet]. ICML-2003 : proceedings. 2003 ;[citado 2024 nov. 05 ] Available from: https://repositorio.usp.br/directbitstream/d50342b6-ec81-4054-a7b6-c8e04caa3ed2/Cozman-2003-semi%20supervised%20learning%20and%20model%20search.pdf
Vancouver
Cozman FG, Cohen I, Cirelo MC. Semi-supervised learning and model search [Internet]. ICML-2003 : proceedings. 2003 ;[citado 2024 nov. 05 ] Available from: https://repositorio.usp.br/directbitstream/d50342b6-ec81-4054-a7b6-c8e04caa3ed2/Cozman-2003-semi%20supervised%20learning%20and%20model%20search.pdf
Trabalho de evento
Learning bayesian network classifiers for facial expression recognition using both labeled and unlabeled data (2003)
Cohen, Ira; Sebe, Nicu; Cozman, Fabio Gagliardi ; Cirelo, Marcelo Cesar; Huang, Thomas S.
Source: CVRP 2003 : proceedings.. Conference titles: IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Unidade: EP
Subjects: APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL, VISÃO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COHEN, Ira et al. Learning bayesian network classifiers for facial expression recognition using both labeled and unlabeled data. 2003, Anais.. Los Alamitos, Calif.: IEEE Computer Society Press, 2003. Disponível em: https://repositorio.usp.br/directbitstream/eafe0cfc-636f-4294-abc1-14b6ac33e903/Cozman-2003-Learning%20bayesian%20network%20classifiers%20for%20facial.pdf. Acesso em: 05 nov. 2024.
APA
Cohen, I., Sebe, N., Cozman, F. G., Cirelo, M. C., & Huang, T. S. (2003). Learning bayesian network classifiers for facial expression recognition using both labeled and unlabeled data. In CVRP 2003 : proceedings.. Los Alamitos, Calif.: IEEE Computer Society Press. Recuperado de https://repositorio.usp.br/directbitstream/eafe0cfc-636f-4294-abc1-14b6ac33e903/Cozman-2003-Learning%20bayesian%20network%20classifiers%20for%20facial.pdf
NLM
Cohen I, Sebe N, Cozman FG, Cirelo MC, Huang TS. Learning bayesian network classifiers for facial expression recognition using both labeled and unlabeled data [Internet]. CVRP 2003 : proceedings. 2003 ;[citado 2024 nov. 05 ] Available from: https://repositorio.usp.br/directbitstream/eafe0cfc-636f-4294-abc1-14b6ac33e903/Cozman-2003-Learning%20bayesian%20network%20classifiers%20for%20facial.pdf
Vancouver
Cohen I, Sebe N, Cozman FG, Cirelo MC, Huang TS. Learning bayesian network classifiers for facial expression recognition using both labeled and unlabeled data [Internet]. CVRP 2003 : proceedings. 2003 ;[citado 2024 nov. 05 ] Available from: https://repositorio.usp.br/directbitstream/eafe0cfc-636f-4294-abc1-14b6ac33e903/Cozman-2003-Learning%20bayesian%20network%20classifiers%20for%20facial.pdf
Trabalho de evento
Unlabeled data can degrade classification performance of generative classifiers (2002)
Cozman, Fabio Gagliardi ; Cohen, Ira
Source: FLAIRS 2002 : proceedings. Conference titles: International Florida Articial Intelligence Research Society Conference. Unidade: EP
Subjects: CLASSIFICAÇÃO (DANOS), APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COZMAN, Fabio Gagliardi e COHEN, Ira. Unlabeled data can degrade classification performance of generative classifiers. 2002, Anais.. Menlo Park, California: AAAI Press, 2002. Disponível em: https://repositorio.usp.br/directbitstream/66d32e74-0b28-4fc0-92bb-13bce47ea766/Cozman-2002-Unlabeled%20data%20can%20degrade%20classification%20performance.pdf. Acesso em: 05 nov. 2024.
APA
Cozman, F. G., & Cohen, I. (2002). Unlabeled data can degrade classification performance of generative classifiers. In FLAIRS 2002 : proceedings. Menlo Park, California: AAAI Press. Recuperado de https://repositorio.usp.br/directbitstream/66d32e74-0b28-4fc0-92bb-13bce47ea766/Cozman-2002-Unlabeled%20data%20can%20degrade%20classification%20performance.pdf
NLM
Cozman FG, Cohen I. Unlabeled data can degrade classification performance of generative classifiers [Internet]. FLAIRS 2002 : proceedings. 2002 ;[citado 2024 nov. 05 ] Available from: https://repositorio.usp.br/directbitstream/66d32e74-0b28-4fc0-92bb-13bce47ea766/Cozman-2002-Unlabeled%20data%20can%20degrade%20classification%20performance.pdf
Vancouver
Cozman FG, Cohen I. Unlabeled data can degrade classification performance of generative classifiers [Internet]. FLAIRS 2002 : proceedings. 2002 ;[citado 2024 nov. 05 ] Available from: https://repositorio.usp.br/directbitstream/66d32e74-0b28-4fc0-92bb-13bce47ea766/Cozman-2002-Unlabeled%20data%20can%20degrade%20classification%20performance.pdf

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