Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Marine Depecker"'
A nonlinear semantic-preserving projection approach to visualize multivariate periodical time series
Autor:
Pierre Blanchart, Marine Depecker
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Neural Networks and Learning Systems, 2023, 25 (6), pp.1053-1070. ⟨10.1109/TNNLS.2013.2285928⟩
IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2014, 25 (6), pp.1053-1070. ⟨10.1109/TNNLS.2013.2285928⟩
IEEE Transactions on Neural Networks and Learning Systems, 2023, 25 (6), pp.1053-1070. ⟨10.1109/TNNLS.2013.2285928⟩
IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2014, 25 (6), pp.1053-1070. ⟨10.1109/TNNLS.2013.2285928⟩
A major drawback of nonlinear dimensionality reduction (DR) techniques is their inability to preserve some authentic information from the source domain, leading to projections that are often hard to interpret when it comes to observing anything other
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b82b4e2a2b469b0e8820c7c48135df5
https://cea.hal.science/cea-01828347/document
https://cea.hal.science/cea-01828347/document
In this paper, we address the estimation of the sensitivity indices called "Shapley eects". These sensitivity indices enable to handle dependent input variables. The Shapley eects are generally dicult to estimate, but they are easily computable in th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e6146a659b533b1efc8ed6b55448ada
http://arxiv.org/abs/2006.02087
http://arxiv.org/abs/2006.02087
The Shapley effects are global sensitivity indices: they quantify the impact of each input variable on the output variable in a model. In this work, we suggest new estimators of these sensitivity indices. When the input distribution is known, we inve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ed104e7ea3056ab1893a5742c6babdb
https://hal.archives-ouvertes.fr/hal-01962010v2/file/Shapley_estimation.pdf
https://hal.archives-ouvertes.fr/hal-01962010v2/file/Shapley_estimation.pdf
Publikováno v:
Pattern Analysis and Applications. 16:475-496
The TreeRank algorithm was recently proposed in [1] and [2] as a scoring-based method based on recursive partitioning of the input space. This tree induction algorithm builds orderings by recursively optimizing the Receiver Operating Characteristic c
Publikováno v:
2011 Tenth International Conference on Machine Learning and Applications (ICMLA 2011)
2011 Tenth International Conference on Machine Learning and Applications (ICMLA 2011), Dec 2011, Honolulu, United States. pp.384-387, ⟨10.1109/ICMLA.2011.185⟩
ICMLA (2)
2011 Tenth International Conference on Machine Learning and Applications (ICMLA 2011), Dec 2011, Honolulu, United States. pp.384-387, ⟨10.1109/ICMLA.2011.185⟩
ICMLA (2)
International audience; Multiple kernel learning (MKL) provides flexibility by considering multiple data views and by searching for the best data representation through a combination of kernels. Clinical applications of neuroimaging have seen recent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::860055a4e355bb7f06eef74f8cd5c2e5
https://hal.archives-ouvertes.fr/hal-02509898
https://hal.archives-ouvertes.fr/hal-02509898
Publikováno v:
Revue des Sciences et Technologies de l'Information-Série RIA : Revue d'Intelligence Artificielle
Revue des Sciences et Technologies de l'Information-Série RIA : Revue d'Intelligence Artificielle, 2011, 25 (3), pp.345-368. ⟨10.3166/ria.25.345-368⟩
Revue des Sciences et Technologies de l'Information-Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2011, 25 (3), pp.345-368. ⟨10.3166/ria.25.345-368⟩
Revue des Sciences et Technologies de l'Information-Série RIA : Revue d'Intelligence Artificielle, 2011, 25 (3), pp.345-368. ⟨10.3166/ria.25.345-368⟩
Revue des Sciences et Technologies de l'Information-Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2011, 25 (3), pp.345-368. ⟨10.3166/ria.25.345-368⟩
In a wide variety of applications, where the data X ∈ X that must be processed characterize instances to which binary labels Y ∈ {-1, +1} are randomly assigned, the goal of statistical learning does not reduce to find the likeliest label for a gi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84bb045cb47915c4d4a41093a4315770
https://telecom-paris.hal.science/hal-02107303
https://telecom-paris.hal.science/hal-02107303
Publikováno v:
Machine Learning
Machine Learning, Springer Verlag, 2010, 43 (1), pp.31-69
Machine Learning, Springer Verlag, 2010, 43 (1), pp.31-69
Recursive partitioning methods are among the most popular techniques in machine learning. The purpose of this paper is to investigate how to adapt this methodology to the bipartite ranking problem. Following in the footsteps of the TreeRank approach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7dd6415cac39d48cd91af2382047b8c
https://hal.archives-ouvertes.fr/hal-00416054/document
https://hal.archives-ouvertes.fr/hal-00416054/document
Publikováno v:
2009 International Conference on Machine Learning and Applications (ICMLA)
2009 International Conference on Machine Learning and Applications (ICMLA), Dec 2009, Miami, United States. pp.658-663, ⟨10.1109/ICMLA.2009.14⟩
ICMLA
2009 International Conference on Machine Learning and Applications (ICMLA), Dec 2009, Miami, United States. pp.658-663, ⟨10.1109/ICMLA.2009.14⟩
ICMLA
It has recently been shown how to extend successfully decision tree induction algorithms to bipartite ranking [1]. The major drawbacks of tree-based prediction rules, instability and lack of smoothness namely, are however exacerbated by the global na
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::113a88976f0c08fc9dffc54b50b031a2
https://hal.telecom-paris.fr/hal-02107271
https://hal.telecom-paris.fr/hal-02107271