Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Rémi Gilleron"'
Autor:
Jean-Yves Marion, Rémi Gilleron, Gilles Dowek, Serge Grigorieff, Simon Perdrix, Olivier Bournez, Sophie Tison
Publikováno v:
A Guided Tour of Artificial Intelligence Research ISBN: 9783030061692
A Guided Tour of Artificial Intelligence Research-Volume III: Interfaces and Applications of Artificial Intelligence (10.1007/978-3-030-06170-8)
A Guided Tour of Artificial Intelligence Research-Volume III: Interfaces and Applications of Artificial Intelligence (10.1007/978-3-030-06170-8), Springer International Publishing, pp.1-50, 2020, ⟨10.1007/978-3-030-06170-8_1⟩
A Guided Tour of Artificial Intelligence Research-Volume III: Interfaces and Applications of Artificial Intelligence (10.1007/978-3-030-06170-8)
A Guided Tour of Artificial Intelligence Research-Volume III: Interfaces and Applications of Artificial Intelligence (10.1007/978-3-030-06170-8), Springer International Publishing, pp.1-50, 2020, ⟨10.1007/978-3-030-06170-8_1⟩
International audience; This chapter deals with a question in the very core of IA: what can be computed by a machine? An agreement has been reached on the answer brought by Alan Turing in 1936. Indeed, all other proposed approaches have led to exactl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::714369ba9254ad8cb7b4b6e981c4955a
https://doi.org/10.1007/978-3-030-06170-8_1
https://doi.org/10.1007/978-3-030-06170-8_1
Autor:
Olivier Bournez, Jean-Yves Marion, Simon Perdrix, Sophie Tison, Rémi Gilleron, Gilles Dowek, Serge Grigorieff
Publikováno v:
A Guided Tour of Artificial Intelligence Research-Volume III: Interfaces and Applications of Artificial Intelligence (10.1007/978-3-030-06170-8)
A Guided Tour of Artificial Intelligence Research-Volume III: Interfaces and Applications of Artificial Intelligence (10.1007/978-3-030-06170-8), Springer International Publishing, 2020
A Guided Tour of Artificial Intelligence Research ISBN: 9783030061692
A Guided Tour of Artificial Intelligence Research-Volume III: Interfaces and Applications of Artificial Intelligence (10.1007/978-3-030-06170-8), Springer International Publishing, 2020
A Guided Tour of Artificial Intelligence Research ISBN: 9783030061692
How much time, space and/or hardware resource does require an algorithm? Such questions lead to surprising results: conceptual simplicity does not always go along with efficiency. A lot of quite natural questions remain open, e.g., the famous P \(=\)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::053d30a7fe3451d69284bd3b9311400c
https://hal.archives-ouvertes.fr/hal-02995771
https://hal.archives-ouvertes.fr/hal-02995771
Publikováno v:
Machine Learning
Machine Learning, 2007, Machine Learning, 66 (1), pp.33-67. ⟨10.1007/s10994-006-9613-8⟩
Machine Learning, 2007, Machine Learning, 66 (1), pp.33-67. ⟨10.1007/s10994-006-9613-8⟩
International audience; We develop new algorithms for learning monadic node selection queries in unranked trees from annotated examples, and apply them to visually interactive Web information extraction. We propose to represent monadic queries by bot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c8ca0dda223490fee00e3e55ec8258c
https://doi.org/10.1007/s10994-006-9613-8
https://doi.org/10.1007/s10994-006-9613-8
Publikováno v:
Conférence Francophone sur l'Apprentissage Automatique (Cap 2014)
Conférence Francophone sur l'Apprentissage Automatique (Cap 2014), Jul 2014, Saint-Etienne, France. ⟨10.1007/978-3-662-44851-9_42⟩
Machine Learning and Knowledge Discovery in Databases ISBN: 9783662448502
ECML/PKDD (2)
ECML/PKDD-7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
ECML/PKDD-7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2014, Nancy, France
Conférence Francophone sur l'Apprentissage Automatique (Cap 2014), Jul 2014, Saint-Etienne, France. ⟨10.1007/978-3-662-44851-9_42⟩
Machine Learning and Knowledge Discovery in Databases ISBN: 9783662448502
ECML/PKDD (2)
ECML/PKDD-7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
ECML/PKDD-7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2014, Nancy, France
Paper accepted for publication at ECML/PKDD 2014; International audience; We introduce hypernode graphs as weighted binary relations between sets of nodes: a hypernode is a set of nodes, a hyperedge is a pair of hypernodes, and each node in a hyperno
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10ee46800d9320c13136a8cff5ef115b
https://hal.inria.fr/hal-01104618
https://hal.inria.fr/hal-01104618
Publikováno v:
The 12th International Conference on Machine Learning and Applications (ICMLA'13)
The 12th International Conference on Machine Learning and Applications (ICMLA'13), Dec 2013, Miami, United States
ICMLA (2)
The 12th International Conference on Machine Learning and Applications (ICMLA'13), Dec 2013, Miami, United States
ICMLA (2)
International audience; This paper studies the problem of learning from a set of input graphs, each of them representing a different relation over the same set of nodes. Our goal is to merge those input graphs by embedding them into an Euclidean spac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e450853eb1991f536ea7a5b21606084
https://inria.hal.science/hal-00913237/file/main.pdf
https://inria.hal.science/hal-00913237/file/main.pdf
Publikováno v:
Information and Computation
Information and Computation, 1999, 149 (1), pp.1--41
Information and Computation, 1999, 149 (1), pp.1--41
International audience; We define a new class of automata which is an acceptor model for mappings from the set of terms T? over a ranked alphabet ? into a set E of labels. When E is a set of tuples of binary values, an automaton can be viewed as an a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc3944f39946a59ee0fe8521431eb3df
https://doi.org/10.1006/inco.1998.2747
https://doi.org/10.1006/inco.1998.2747
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783642334597
ECML/PKDD (1)
ECML/PKDD-European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases-2012
ECML/PKDD-European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases-2012, 2012, Bristol, United Kingdom
ECML/PKDD (1)
ECML/PKDD-European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases-2012
ECML/PKDD-European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases-2012, 2012, Bristol, United Kingdom
International audience; We address the problem of multi-task learning with no label correspondence among tasks. Learning multiple related tasks simultane- ously, by exploiting their shared knowledge can improve the predictive performance on every tas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d93e97da38df9157502b019d9a40fefd
https://doi.org/10.1007/978-3-642-33460-3_49
https://doi.org/10.1007/978-3-642-33460-3_49
Publikováno v:
The Ninth International Conference on Machine Learning and Applications (ICMLA 2010)
The Ninth International Conference on Machine Learning and Applications (ICMLA 2010), Dec 2010, Hayatt Regency Bethesda, Washington DC, United States
ICMLA
The Ninth International Conference on Machine Learning and Applications (ICMLA 2010), Dec 2010, Hayatt Regency Bethesda, Washington DC, United States
ICMLA
International audience; Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a novel multi-task learning algorithm called MT-Adaboost: it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82aa484d00f75d0a98265bbe57db0636
https://inria.hal.science/inria-00524718
https://inria.hal.science/inria-00524718
Publikováno v:
SAC
Adapting keyword search to XML data has been attractive recently, generalized as XML Keyword Search (XKS). Its fundamental task is to retrieve meaningful and concise result for the given keyword query, and [1] is the latest work which returns the fra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ca4aa234a9c9153785ce5f8a51c72cf
https://doi.org/10.1145/1529282.1529627
https://doi.org/10.1145/1529282.1529627
Publikováno v:
Database Systems for Advanced Applications ISBN: 9783642008863
DASFAA
DASFAA
This paper proposes a new effective filtering mechanism for pruning the uninteresting nodes implied in the SLCA-based (Smallest LCA --- Lowest Common Ancestor) fragments for XML keyword search. Its fundamental concept is the valid contributor. Given
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56927d929872ee493286637d073a5f2e
https://doi.org/10.1007/978-3-642-00887-0_47
https://doi.org/10.1007/978-3-642-00887-0_47