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Cooperative parallel particle filters for online model selection and applications to urban mobility
Cooperative parallel particle filters for online model selection and applications to urban mobility
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Artigo 		Adicionar ao Meu Espaço

Cooperative parallel particle filters for online model selection and applications to urban mobility

L. Martino (Luca Martino) Jesse Read (David Luengo); V Elvira (Vıctor Elvira); Francisco Louzada

Digital Signal Processing Amsterdam : Elsevier v. 60, p. 172-185, Jan. 2017

Amsterdam 2017

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD 2834708 )(Acessar)

2
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning
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An empirical analysis of binary transformation strategies and base algorithms for multi-label learning

Adriano Rivolli Jesse Read; Carlos Soares; Bernhard Pfahringer; André Carlos Ponce de Leon Ferreira de Carvalho

Machine Learning Dordrecht : Springer v. 109, n. 8, p. 1509-1563, Aug. 2020

Dordrecht 2020

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-2998614 )(Acessar)

3
Data streams are time series challenging assumptions
Data streams are time series challenging assumptions
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Artigo de Congresso 		Adicionar ao Meu Espaço

Data streams are time series challenging assumptions

Jesse Read Ricardo A Rios; Tatiane Nogueira; Rodrigo Fernandes de Mello; Brazilian Conference on Intelligent Systems - BRACIS (9. 2020 Rio Grande)

Lecture Notes in Artificial Intelligence Cham : Springer v. 12320, p. 529-543, 2020

Cham Springer 2020

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-3008278 )(Acessar)

4
River machine learning for streaming data in Python
River machine learning for streaming data in Python
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River machine learning for streaming data in Python

Jacob Montiel Max Halford; Saulo Martiello Mastelini; Geoffrey Bolmier; Raphael Sourty; Robin Vaysse; Adil Zouitine; Heitor Murilo Gomes; Jesse Read; Talel Abdessalem; Albert Bifet

Journal of Machine Learning Research Brookline v. 22, p. 1-8, 2021

Brookline 2021

Acesso online. A biblioteca também possui exemplares impressos.

5
Classifier chains for multi-label classification
Classifier chains for multi-label classification
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Classifier chains for multi-label classification

Read, Jesse ; Pfahringer, Bernhard ; Holmes, Geoff ; Frank, Eibe

Machine learning, 2011-12, Vol.85 (3), p.333-359 [Periódico revisado por pares]

Boston: Springer US

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6
Cooperative parallel particle filters for online model selection and applications to urban mobility
Cooperative parallel particle filters for online model selection and applications to urban mobility
Material Type:
Artigo 		Adicionar ao Meu Espaço

Cooperative parallel particle filters for online model selection and applications to urban mobility

Martino, Luca ; Read, Jesse ; Elvira, Víctor ; Louzada, Francisco

Digital signal processing, 2017-01, Vol.60, p.172-185 [Periódico revisado por pares]

Elsevier Inc

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7
Scalable multi-output label prediction: From classifier chains to classifier trellises
Scalable multi-output label prediction: From classifier chains to classifier trellises
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Scalable multi-output label prediction: From classifier chains to classifier trellises

Read, Jesse ; Martino, Luca ; Olmos, Pablo M. ; Luengo, David

Pattern recognition, 2015-06, Vol.48 (6), p.2096-2109 [Periódico revisado por pares]

Elsevier Ltd

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8
A joint introduction to Gaussian Processes and Relevance Vector Machines with connections to Kalman filtering and other kernel smoothers
A joint introduction to Gaussian Processes and Relevance Vector Machines with connections to Kalman filtering and other kernel smoothers
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A joint introduction to Gaussian Processes and Relevance Vector Machines with connections to Kalman filtering and other kernel smoothers

Martino, Luca ; Read, Jesse

Information fusion, 2021-10, Vol.74, p.17-38 [Periódico revisado por pares]

Elsevier B.V

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9
From multi-label learning to cross-domain transfer: a model-agnostic approach
From multi-label learning to cross-domain transfer: a model-agnostic approach
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From multi-label learning to cross-domain transfer: a model-agnostic approach

Read, Jesse

Applied intelligence (Dordrecht, Netherlands), 2023-11, Vol.53 (21), p.25135-25153 [Periódico revisado por pares]

New York: Springer US

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10
Structure and influence in a global capital–ownership network
Structure and influence in a global capital–ownership network
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Structure and influence in a global capital–ownership network

Khalife, Sammy ; Read, Jesse ; Vazirgiannis, Michalis

Applied network science, 2021-02, Vol.6 (1), p.1-21, Article 16 [Periódico revisado por pares]

Cham: Springer International Publishing

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