A Spectral Method that Worked Well in the SPiCe'16 Competition

Liza, Farhana Ferdousi, Grzes, Marek (2016) A Spectral Method that Worked Well in the SPiCe'16 Competition. In: Verwer, Sicco and van Zaanen, Menno and Smetsers, Rick, eds. Journal of Machine Learning Research. Volume 57: Proceedings of The 13th International Conference on Grammatical Inference. JMLR: Workshop and Conference Proceedings , 57. pp. 143-148. Journal of Machine Learning Research (KAR id:57327)

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Official URL: http://www.jmlr.org/proceedings/papers/v57/

Abstract

We present methods used in our submission to the Sequence Prediction ChallengE (SPiCe’16) 1 .

The two methods used to solve the competition tasks were spectral learning and a count

based method. Spectral learning led to better results on most of the problems.

Item Type:	Conference or workshop item (Proceeding)
Uncontrolled keywords:	Spectral Learning, Rank, Sequence Prediction, Hyperparameters
Subjects:	Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User:	Marek Grzes
Date Deposited:	16 Sep 2016 14:26 UTC
Last Modified:	05 Nov 2024 10:47 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/57327 (The current URI for this page, for reference purposes)

University of Kent Author Information

Liza, Farhana Ferdousi.

Creator's ORCID:
CReDIT Contributor Roles:

Grzes, Marek.

Creator's ORCID:	https://orcid.org/0000-0003-4901-1539
CReDIT Contributor Roles:

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