Multitask Similarity Cluster

Zhen Xing Li; Wei Hua Li

doi:10.4028/www.scientific.net/AMR.765-767.1662

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 765-767Multitask Similarity Cluster

Multitask Similarity Cluster

Abstract:

Single task learning is widely used training in artificial neural network. Before, people usually see other tasks as noise in same learning machine. However, multitask learning, proposed by Rich Caruana, sees simultaneously training several correlated tasks is helpful to improve single tasks performance. In this paper, we propose a new neural network multitask similarity cluster. Combined with hellinger distance, multitask similarity cluster can estimate distances among clusters more accurate. Experimental results show multitask learning is helpful to improve performance of single task and multitask similarity cluster can get satisfactory result.

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Periodical:

Advanced Materials Research (Volumes 765-767)

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1662-1666

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.765-767.1662

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Online since:

September 2013

Authors:

Zhen Xing Li, Wei Hua Li

Keywords:

Artificial Neural Network (ANN), Hellinger Distance, Multitask Learning

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