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Trabalho de evento-anais periodico
Active inference of extended finite state models of software systems (2023)
Groz, Roland ; Oriat, Catherine ; Vega, Germán ; Simão, Adenilso da Silva ; Foster, Michael; Walkinshaw, Neil
Source: Proceedings of Machine Learning Research - PMLR. Conference titles: International Conference on Grammatical Inference - ICGI. Unidade: ICMC
Subjects: APRENDIZAGEM, PROGRAMAÇÃO GENÉTICA, INFERÊNCIA, ENGENHARIA DE SOFTWARE
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ABNT
GROZ, Roland et al. Active inference of extended finite state models of software systems. Proceedings of Machine Learning Research - PMLR. Brookline: Microtome Publishing. Disponível em: https://proceedings.mlr.press/v217/groz23a.html. Acesso em: 18 nov. 2024. , 2023
APA
Groz, R., Oriat, C., Vega, G., Simão, A. da S., Foster, M., & Walkinshaw, N. (2023). Active inference of extended finite state models of software systems. Proceedings of Machine Learning Research - PMLR. Brookline: Microtome Publishing. Recuperado de https://proceedings.mlr.press/v217/groz23a.html
NLM
Groz R, Oriat C, Vega G, Simão A da S, Foster M, Walkinshaw N. Active inference of extended finite state models of software systems [Internet]. Proceedings of Machine Learning Research - PMLR. 2023 ; 217 265-269.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v217/groz23a.html
Vancouver
Groz R, Oriat C, Vega G, Simão A da S, Foster M, Walkinshaw N. Active inference of extended finite state models of software systems [Internet]. Proceedings of Machine Learning Research - PMLR. 2023 ; 217 265-269.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v217/groz23a.html
Trabalho de evento-anais periodico
Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification (2022)
Baz, Adrian El; Ullah, Ihsan; Alcobaça, Edesio ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Chen, Hong; Ferreira, Fábio; Gouk, Henry; Guan, Chaoyu; Guyon, Isabelle; Hospedales, Timothy; Hu, Shell; Huisman, Mike ; Hutter, Frank ; Liu, Zhengying; Mohr, Felix ; Öztürk, Ekrem ; Rijn, Jan N. van ; Sun, Haozhe; Wang, Xin; Zhu, Wenwu
Source: Proceedings of Machine Learning Research : PMLR. Conference titles: Conference on Neural Information Processing Systems - NeurIPS. Unidade: ICMC
Assunto: APRENDIZADO COMPUTACIONAL
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ABNT
BAZ, Adrian El et al. Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Disponível em: https://proceedings.mlr.press/v176/el-baz22a.html. Acesso em: 18 nov. 2024. , 2022
APA
Baz, A. E., Ullah, I., Alcobaça, E., Carvalho, A. C. P. de L. F. de, Chen, H., Ferreira, F., et al. (2022). Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Recuperado de https://proceedings.mlr.press/v176/el-baz22a.html
NLM
Baz AE, Ullah I, Alcobaça E, Carvalho ACP de LF de, Chen H, Ferreira F, Gouk H, Guan C, Guyon I, Hospedales T, Hu S, Huisman M, Hutter F, Liu Z, Mohr F, Öztürk E, Rijn JN van, Sun H, Wang X, Zhu W. Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 176 80-96.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v176/el-baz22a.html
Vancouver
Baz AE, Ullah I, Alcobaça E, Carvalho ACP de LF de, Chen H, Ferreira F, Gouk H, Guan C, Guyon I, Hospedales T, Hu S, Huisman M, Hutter F, Liu Z, Mohr F, Öztürk E, Rijn JN van, Sun H, Wang X, Zhu W. Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 176 80-96.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v176/el-baz22a.html
Trabalho de evento-anais periodico
Detecting and mitigating issues in image-based COVID-19 diagnosis (2022)
Silva, João Marcos Cardoso da; Rezende, Pedro Martelleto Bressane; Ponti, Moacir Antonelli
Source: Proceedings of Machine Learning Research : PMLR. Conference titles: International Conference on Machine Learning - ICML. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR IMAGEM, COVID-19
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ABNT
SILVA, João Marcos Cardoso da e REZENDE, Pedro Martelleto Bressane e PONTI, Moacir Antonelli. Detecting and mitigating issues in image-based COVID-19 diagnosis. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Disponível em: https://proceedings.mlr.press/v184/silva22a.html. Acesso em: 18 nov. 2024. , 2022
APA
Silva, J. M. C. da, Rezende, P. M. B., & Ponti, M. A. (2022). Detecting and mitigating issues in image-based COVID-19 diagnosis. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Recuperado de https://proceedings.mlr.press/v184/silva22a.html
NLM
Silva JMC da, Rezende PMB, Ponti MA. Detecting and mitigating issues in image-based COVID-19 diagnosis [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 184 127-135.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v184/silva22a.html
Vancouver
Silva JMC da, Rezende PMB, Ponti MA. Detecting and mitigating issues in image-based COVID-19 diagnosis [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 184 127-135.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v184/silva22a.html
Trabalho de evento-anais periodico
YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone (2022)
Casanova, Edresson ; Weber, Julian; Shulby, Christopher Dane ; Candido Junior, Arnaldo ; Gölge, Eren; Ponti, Moacir Antonelli
Source: Proceedings of Machine Learning Research : PMLR. Conference titles: International Conference on Machine Learning - ICML. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DA FALA, SÍNTESE DE FALA
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ABNT
CASANOVA, Edresson et al. YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Disponível em: https://proceedings.mlr.press/v162/casanova22a.html. Acesso em: 18 nov. 2024. , 2022
APA
Casanova, E., Weber, J., Shulby, C. D., Candido Junior, A., Gölge, E., & Ponti, M. A. (2022). YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Recuperado de https://proceedings.mlr.press/v162/casanova22a.html
NLM
Casanova E, Weber J, Shulby CD, Candido Junior A, Gölge E, Ponti MA. YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 162 2709-2720.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v162/casanova22a.html
Vancouver
Casanova E, Weber J, Shulby CD, Candido Junior A, Gölge E, Ponti MA. YourTTS: towards zero-shot multi-speaker TTS and zero-shot voice conversion for everyone [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 162 2709-2720.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v162/casanova22a.html
Trabalho de evento-anais periodico
GALE: globally assessing local explanations (2022)
Xenopoulos, Peter ; Silva, Claudio; Chan, Gromit Yeuk-Yin ; Doraiswamy, Harish ; Nonato, Luis Gustavo ; Barr, Brian; Silva, Claudio
Source: Proceedings of Machine Learning Research - PMLR. Conference titles: Workshop on Topology, Algebra, and Geometry in Machine Learning. Unidade: ICMC
Subjects: TOPOLOGIA, PREDIÇÃO, FRAMEWORKS
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ABNT
XENOPOULOS, Peter et al. GALE: globally assessing local explanations. Proceedings of Machine Learning Research - PMLR. Brookline: Microtome Publishing. Disponível em: https://proceedings.mlr.press/v196/xenopoulos22a.html. Acesso em: 18 nov. 2024. , 2022
APA
Xenopoulos, P., Silva, C., Chan, G. Y. -Y., Doraiswamy, H., Nonato, L. G., Barr, B., & Silva, C. (2022). GALE: globally assessing local explanations. Proceedings of Machine Learning Research - PMLR. Brookline: Microtome Publishing. Recuperado de https://proceedings.mlr.press/v196/xenopoulos22a.html
NLM
Xenopoulos P, Silva C, Chan GY-Y, Doraiswamy H, Nonato LG, Barr B, Silva C. GALE: globally assessing local explanations [Internet]. Proceedings of Machine Learning Research - PMLR. 2022 ; 196 322-331.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v196/xenopoulos22a.html
Vancouver
Xenopoulos P, Silva C, Chan GY-Y, Doraiswamy H, Nonato LG, Barr B, Silva C. GALE: globally assessing local explanations [Internet]. Proceedings of Machine Learning Research - PMLR. 2022 ; 196 322-331.[citado 2024 nov. 18 ] Available from: https://proceedings.mlr.press/v196/xenopoulos22a.html
Trabalho de evento-anais periodico
Robust analysis of MAP inference in selective sum-product nNetworks (2019)
Villanueva Llerena, Julissa Giuliana ; Mauá, Denis Deratani
Source: Proceedings of Machine Learning Research : PMLR. Conference titles: International Symposium on Imprecise Probabilities: Theories and Applications - ISIPTA. Unidade: IME
Subjects: INTELIGÊNCIA ARTIFICIAL, RACIOCÍNIO PROBABILÍSTICO
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ABNT
VILLANUEVA LLERENA, Julissa Giuliana e MAUÁ, Denis Deratani. Robust analysis of MAP inference in selective sum-product nNetworks. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Disponível em: http://proceedings.mlr.press/v103/villanueva-llerena19a/villanueva-llerena19a.pdf. Acesso em: 18 nov. 2024. , 2019
APA
Villanueva Llerena, J. G., & Mauá, D. D. (2019). Robust analysis of MAP inference in selective sum-product nNetworks. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Recuperado de http://proceedings.mlr.press/v103/villanueva-llerena19a/villanueva-llerena19a.pdf
NLM
Villanueva Llerena JG, Mauá DD. Robust analysis of MAP inference in selective sum-product nNetworks [Internet]. Proceedings of Machine Learning Research : PMLR. 2019 ; 103 430–440.[citado 2024 nov. 18 ] Available from: http://proceedings.mlr.press/v103/villanueva-llerena19a/villanueva-llerena19a.pdf
Vancouver
Villanueva Llerena JG, Mauá DD. Robust analysis of MAP inference in selective sum-product nNetworks [Internet]. Proceedings of Machine Learning Research : PMLR. 2019 ; 103 430–440.[citado 2024 nov. 18 ] Available from: http://proceedings.mlr.press/v103/villanueva-llerena19a/villanueva-llerena19a.pdf
Trabalho de evento-anais periodico
Using adaptive sequences for learning non-resettable FSMs (2019)
Groz, Roland; Bremond, Nicolas; Simão, Adenilso da Silva
Source: Proceedings of Machine Learning Research : PMLR. Conference titles: International Conference on Grammatical Inference - ICGI. Unidade: ICMC
Subjects: ENGENHARIA DE SOFTWARE, ANÁLISE DE ALGORITMOS
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ABNT
GROZ, Roland e BREMOND, Nicolas e SIMÃO, Adenilso da Silva. Using adaptive sequences for learning non-resettable FSMs. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Disponível em: http://proceedings.mlr.press/v93/groz19a/groz19a.pdf. Acesso em: 18 nov. 2024. , 2019
APA
Groz, R., Bremond, N., & Simão, A. da S. (2019). Using adaptive sequences for learning non-resettable FSMs. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Recuperado de http://proceedings.mlr.press/v93/groz19a/groz19a.pdf
NLM
Groz R, Bremond N, Simão A da S. Using adaptive sequences for learning non-resettable FSMs [Internet]. Proceedings of Machine Learning Research : PMLR. 2019 ; 93 30-43.[citado 2024 nov. 18 ] Available from: http://proceedings.mlr.press/v93/groz19a/groz19a.pdf
Vancouver
Groz R, Bremond N, Simão A da S. Using adaptive sequences for learning non-resettable FSMs [Internet]. Proceedings of Machine Learning Research : PMLR. 2019 ; 93 30-43.[citado 2024 nov. 18 ] Available from: http://proceedings.mlr.press/v93/groz19a/groz19a.pdf
Trabalho de evento-anais periodico
On the need of class ratio insensitive drift tests for data streams (2018)
Maletzke, André Gustavo; Reis, Denis dos; Cherman, Everton Alvares; Batista, Gustavo Enrique de Almeida Prado Alves
Source: Proceedings of Machine Learning Research : PMLR. Conference titles: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database - ECML PKDD. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, RECONHECIMENTO DE PADRÕES
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ABNT
MALETZKE, André Gustavo et al. On the need of class ratio insensitive drift tests for data streams. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Disponível em: http://proceedings.mlr.press/v94/maletzke18a.html. Acesso em: 18 nov. 2024. , 2018
APA
Maletzke, A. G., Reis, D. dos, Cherman, E. A., & Batista, G. E. de A. P. A. (2018). On the need of class ratio insensitive drift tests for data streams. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Recuperado de http://proceedings.mlr.press/v94/maletzke18a.html
NLM
Maletzke AG, Reis D dos, Cherman EA, Batista GE de APA. On the need of class ratio insensitive drift tests for data streams [Internet]. Proceedings of Machine Learning Research : PMLR. 2018 ; 94 110-124.[citado 2024 nov. 18 ] Available from: http://proceedings.mlr.press/v94/maletzke18a.html
Vancouver
Maletzke AG, Reis D dos, Cherman EA, Batista GE de APA. On the need of class ratio insensitive drift tests for data streams [Internet]. Proceedings of Machine Learning Research : PMLR. 2018 ; 94 110-124.[citado 2024 nov. 18 ] Available from: http://proceedings.mlr.press/v94/maletzke18a.html
Trabalho de evento-anais periodico
Transfer learning with cluster ensembles (2012)
Acharya, Ayan; Hruschka, Eduardo Raul ; Ghosh, Joydeep; Acharyya, Sreangsu
Source: JMLR: Workshop and Conference Proceedings. Conference titles: International Conference on Machine Learning - ICML. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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ABNT
ACHARYA, Ayan et al. Transfer learning with cluster ensembles. JMLR: Workshop and Conference Proceedings. Brookline: Microtome Publishing. Disponível em: http://jmlr.csail.mit.edu/proceedings/papers/v27/. Acesso em: 18 nov. 2024. , 2012
APA
Acharya, A., Hruschka, E. R., Ghosh, J., & Acharyya, S. (2012). Transfer learning with cluster ensembles. JMLR: Workshop and Conference Proceedings. Brookline: Microtome Publishing. Recuperado de http://jmlr.csail.mit.edu/proceedings/papers/v27/
NLM
Acharya A, Hruschka ER, Ghosh J, Acharyya S. Transfer learning with cluster ensembles [Internet]. JMLR: Workshop and Conference Proceedings. 2012 ; 27 123-133.[citado 2024 nov. 18 ] Available from: http://jmlr.csail.mit.edu/proceedings/papers/v27/
Vancouver
Acharya A, Hruschka ER, Ghosh J, Acharyya S. Transfer learning with cluster ensembles [Internet]. JMLR: Workshop and Conference Proceedings. 2012 ; 27 123-133.[citado 2024 nov. 18 ] Available from: http://jmlr.csail.mit.edu/proceedings/papers/v27/

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