Sunny-as2: Enhancing SUNNY for algorithm selection (extended abstract)

Tong Liu; Roberto Amadini; Maurizio Gabbrielli; Jacopo Mauro

doi:10.24963/ijcai.2022/804

Sunny-as2: Enhancing SUNNY for algorithm selection (extended abstract)

Tong Liu, Roberto Amadini^*, Maurizio Gabbrielli, Jacopo Mauro^*

^*Kontaktforfatter

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

Abstract

SUNNY is a k-nearest neighbors based Algorithm Selection (AS) approach that schedules and runs a number of solvers for a given unforeseen problem. In this work we present sunny-as2, an enhancement of SUNNY for generic AS scenarios that advances the original approach with wrapper-based feature selection, neighborhood-size configuration and a greedy approach to speed-up the training phase. Empirical evidence shows that sunny-as2 is competitive w.r.t. state-of-the-art AS approaches.

Originalsprog	Engelsk
Titel	Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022
Redaktører	Luc De Raedt
Forlag	International Joint Conferences on Artificial Intelligence
Publikationsdato	2022
Sider	5752-5756
ISBN (Elektronisk)	9781956792003
DOI	https://doi.org/10.24963/ijcai.2022/804
Status	Udgivet - 2022
Begivenhed	31st International Joint Conference on Artificial Intelligence, IJCAI 2022 - Vienna, Østrig Varighed: 23. jul. 2022 → 29. jul. 2022

Konference

Konference	31st International Joint Conference on Artificial Intelligence, IJCAI 2022
Land/Område	Østrig
By	Vienna
Periode	23/07/2022 → 29/07/2022
Sponsor	Artificial Intelligence Journal, Didi Chuxing, et al., FinVolution Group, International Joint Conferences on Artificial Intelligence (IJCAI), Shanghai Artificial Intelligence Industry Association

Navn	IJCAI International Joint Conference on Artificial Intelligence
ISSN	1045-0823

Bibliografisk note

Publisher Copyright:
© 2022 International Joint Conferences on Artificial Intelligence. All rights reserved.

Dokumenter og links

10.24963/ijcai.2022/804

Citationsformater

Liu, Tong ; Amadini, Roberto ; Gabbrielli, Maurizio et al. / Sunny-as2 : Enhancing SUNNY for algorithm selection (extended abstract). Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022. red. / Luc De Raedt. International Joint Conferences on Artificial Intelligence, 2022. s. 5752-5756 (IJCAI International Joint Conference on Artificial Intelligence).

@inproceedings{15165410e3474af0beba6a1d353729ef,

title = "Sunny-as2: Enhancing SUNNY for algorithm selection (extended abstract)",

abstract = "SUNNY is a k-nearest neighbors based Algorithm Selection (AS) approach that schedules and runs a number of solvers for a given unforeseen problem. In this work we present sunny-as2, an enhancement of SUNNY for generic AS scenarios that advances the original approach with wrapper-based feature selection, neighborhood-size configuration and a greedy approach to speed-up the training phase. Empirical evidence shows that sunny-as2 is competitive w.r.t. state-of-the-art AS approaches.",

author = "Tong Liu and Roberto Amadini and Maurizio Gabbrielli and Jacopo Mauro",

note = "Publisher Copyright: {\textcopyright} 2022 International Joint Conferences on Artificial Intelligence. All rights reserved.; 31st International Joint Conference on Artificial Intelligence, IJCAI 2022 ; Conference date: 23-07-2022 Through 29-07-2022",

year = "2022",

doi = "10.24963/ijcai.2022/804",

language = "English",

series = "IJCAI International Joint Conference on Artificial Intelligence",

publisher = "International Joint Conferences on Artificial Intelligence",

pages = "5752--5756",

editor = "{De Raedt}, Luc",

booktitle = "Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022",

}

Liu, T, Amadini, R, Gabbrielli, M & Mauro, J 2022, Sunny-as2: Enhancing SUNNY for algorithm selection (extended abstract). i L De Raedt (red.), Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022. International Joint Conferences on Artificial Intelligence, IJCAI International Joint Conference on Artificial Intelligence, s. 5752-5756, 31st International Joint Conference on Artificial Intelligence, IJCAI 2022, Vienna, Østrig, 23/07/2022. https://doi.org/10.24963/ijcai.2022/804

Sunny-as2: Enhancing SUNNY for algorithm selection (extended abstract). / Liu, Tong; Amadini, Roberto; Gabbrielli, Maurizio et al.
Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022. red. / Luc De Raedt. International Joint Conferences on Artificial Intelligence, 2022. s. 5752-5756 (IJCAI International Joint Conference on Artificial Intelligence).

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

TY - GEN

T1 - Sunny-as2

T2 - 31st International Joint Conference on Artificial Intelligence, IJCAI 2022

AU - Liu, Tong

AU - Amadini, Roberto

AU - Gabbrielli, Maurizio

AU - Mauro, Jacopo

PY - 2022

Y1 - 2022

N2 - SUNNY is a k-nearest neighbors based Algorithm Selection (AS) approach that schedules and runs a number of solvers for a given unforeseen problem. In this work we present sunny-as2, an enhancement of SUNNY for generic AS scenarios that advances the original approach with wrapper-based feature selection, neighborhood-size configuration and a greedy approach to speed-up the training phase. Empirical evidence shows that sunny-as2 is competitive w.r.t. state-of-the-art AS approaches.

AB - SUNNY is a k-nearest neighbors based Algorithm Selection (AS) approach that schedules and runs a number of solvers for a given unforeseen problem. In this work we present sunny-as2, an enhancement of SUNNY for generic AS scenarios that advances the original approach with wrapper-based feature selection, neighborhood-size configuration and a greedy approach to speed-up the training phase. Empirical evidence shows that sunny-as2 is competitive w.r.t. state-of-the-art AS approaches.

U2 - 10.24963/ijcai.2022/804

DO - 10.24963/ijcai.2022/804

M3 - Article in proceedings

AN - SCOPUS:85137864451

T3 - IJCAI International Joint Conference on Artificial Intelligence

SP - 5752

EP - 5756

BT - Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022

A2 - De Raedt, Luc

PB - International Joint Conferences on Artificial Intelligence

Y2 - 23 July 2022 through 29 July 2022

ER -

Liu T, Amadini R, Gabbrielli M, Mauro J. Sunny-as2: Enhancing SUNNY for algorithm selection (extended abstract). I De Raedt L, red., Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022. International Joint Conferences on Artificial Intelligence. 2022. s. 5752-5756. (IJCAI International Joint Conference on Artificial Intelligence). doi: 10.24963/ijcai.2022/804

Sunny-as2: Enhancing SUNNY for algorithm selection (extended abstract)

Abstract

Konference

Bibliografisk note

Dokumenter og links

Fingeraftryk

Citationsformater