Multitask Similarity Cluster
2013 ◽
Vol 765-767
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pp. 1662-1666
Keyword(s):
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.
2016 ◽
Vol 29
(11)
◽
pp. 983-989
◽
2017 ◽
Vol 465
◽
pp. 285-288
◽
2013 ◽
Vol 2013
◽
pp. 1-15
◽
2011 ◽
Vol 128-129
◽
pp. 134-137
2015 ◽
Vol 2015
◽
pp. 1-11
◽