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pro vyhledávání: '"Zhang, Ruocong"'
Autor:
Zhang, Ruocong
The goal of this work is to predict the returns of financial assets with statistical learning methods. We are motivated by the problem of stock selection in portfolio management. In particular, we will focus on the prediction of the sign of future re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______166::3dde4e8f94ecc5725e74695019f224c7
https://theses.hal.science/tel-01856339
https://theses.hal.science/tel-01856339
Autor:
Zhang, Ruocong
Publikováno v:
Apprentissage [cs.LG]. Télécom ParisTech, 2014. Français. ⟨NNT : 2014ENST0049⟩
The goal of this work is to predict the returns of financial assets with statistical learning methods. We are motivated by the problem of stock selection in portfolio management. In particular, we will focus on the prediction of the sign of future re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______212::3dde4e8f94ecc5725e74695019f224c7
https://tel.archives-ouvertes.fr/tel-01856339
https://tel.archives-ouvertes.fr/tel-01856339
Autor:
Zhang, Ruocong
Publikováno v:
Apprentissage [cs.LG]. Télécom ParisTech, 2014. Français. ⟨NNT : 2014ENST0049⟩
The goal of this work is to predict the returns of financial assets with statistical learning methods. We are motivated by the problem of stock selection in portfolio management. In particular, we will focus on the prediction of the sign of future re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2592::3dde4e8f94ecc5725e74695019f224c7
https://tel.archives-ouvertes.fr/tel-01856339
https://tel.archives-ouvertes.fr/tel-01856339
Publikováno v:
[Research Report] 2013
We propose multitask Laplacian learning, a new method for jointly learning clusters of closely related tasks. Unlike standard multitask methodologies, the graph of relations among the tasks is not assumed to be known a priori, but is learned by the m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ecdcea5e020560643a1d97740bd37eaf
https://hal.inria.fr/hal-00940321/document
https://hal.inria.fr/hal-00940321/document