Casa Batlo is in Passeig de Gracia or landmarking the expertise space

Hilan Bensusan; Christophe Giraud-Carrier

Casa Batlo is in Passeig de Gracia or landmarking the expertise space

Hilan Bensusan
, Christophe Giraud-Carrier

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

Task description is crucial not only to every meta-learning enterprise but also to related endeavours like transfer of learning. This paper evaluates the performance of a newly introduced method of task description, landmarking, in a supervised meta-learning scenario. The method relies on correlations between simple and more sophisticated learning algorithms to select the best learner for a task. The results compare favourably with an information-based method and suggest that landmarking holds promise.

Translated title of the contribution	Casa Batlo is in Passeig de Gracia or landmarking the expertise space
Original language	English
Title of host publication	Proceedings of the ECML'2000 workshop on Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Combination
Publisher	ECML'2000
Pages	29 - 47
Number of pages	18
Publication status	Published - 2000

Bibliographical note

Other page information: 29-47
Conference Proceedings/Title of Journal: Proceedings of the ECML'2000 workshop on Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Combination
Other identifier: 1000470

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@inproceedings{9e08d39c2d3247febbccd30db25d12a7,

title = "Casa Batlo is in Passeig de Gracia or landmarking the expertise space",

abstract = "Task description is crucial not only to every meta-learning enterprise but also to related endeavours like transfer of learning. This paper evaluates the performance of a newly introduced method of task description, landmarking, in a supervised meta-learning scenario. The method relies on correlations between simple and more sophisticated learning algorithms to select the best learner for a task. The results compare favourably with an information-based method and suggest that landmarking holds promise. ",

author = "Hilan Bensusan and Christophe Giraud-Carrier",

note = "Other page information: 29-47 Conference Proceedings/Title of Journal: Proceedings of the ECML'2000 workshop on Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Combination Other identifier: 1000470",

year = "2000",

language = "English",

pages = "29 -- 47",

booktitle = "Proceedings of the ECML'2000 workshop on Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Combination",

publisher = "ECML'2000",

}

Casa Batlo is in Passeig de Gracia or landmarking the expertise space. / Bensusan, Hilan; Giraud-Carrier, Christophe.
Proceedings of the ECML'2000 workshop on Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Combination. ECML'2000, 2000. p. 29 - 47.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Casa Batlo is in Passeig de Gracia or landmarking the expertise space

AU - Bensusan, Hilan

AU - Giraud-Carrier, Christophe

N1 - Other page information: 29-47 Conference Proceedings/Title of Journal: Proceedings of the ECML'2000 workshop on Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Combination Other identifier: 1000470

PY - 2000

Y1 - 2000

N2 - Task description is crucial not only to every meta-learning enterprise but also to related endeavours like transfer of learning. This paper evaluates the performance of a newly introduced method of task description, landmarking, in a supervised meta-learning scenario. The method relies on correlations between simple and more sophisticated learning algorithms to select the best learner for a task. The results compare favourably with an information-based method and suggest that landmarking holds promise.

AB - Task description is crucial not only to every meta-learning enterprise but also to related endeavours like transfer of learning. This paper evaluates the performance of a newly introduced method of task description, landmarking, in a supervised meta-learning scenario. The method relies on correlations between simple and more sophisticated learning algorithms to select the best learner for a task. The results compare favourably with an information-based method and suggest that landmarking holds promise.

M3 - Conference Contribution (Conference Proceeding)

SP - 29

EP - 47

BT - Proceedings of the ECML'2000 workshop on Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Combination

PB - ECML'2000

ER -

Casa Batlo is in Passeig de Gracia or landmarking the expertise space

Abstract

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