NDLI: Tensor classification network

Content Provider	IEEE Xplore Digital Library
Author	Yi-Ting Bao Jen-Tzung Chien
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan (Yi-Ting Bao; Jen-Tzung Chien)
Abstract	The growing interests in multi-way data analysis have made the tensor factorization and classification a crucial issue in machine learning for signal processing. Conventional neural network (NN) classifier is estimated from a set of input vectors. The multi-way data are unfolded as high-dimensional vectors for model training. The classification performance is constrained because the neighboring temporal or spatial information in different ways is lost in the trained NN classifier. More parameters are required to learn the complicated data structure. This paper presents a new tensor classification network (TCN) which combines the tensor factorization and the NN classification for multi-way feature extraction and classification. We generalize from NN classifier to TCN where the multi-way information is preserved through projecting the input tensors into latent tensors. The projection over tensor space is efficiently characterized so that a very compact classifier can be achieved. Experimental results on image recognition demonstrate that TCN attains comparable classification performance but with very few parameters (as small as 6.7%) compared with NN classifier.
Starting Page	1
Ending Page	6
File Size	733083
Page Count	6
File Format	PDF
ISBN	9781467374545
DOI	10.1109/MLSP.2015.7324360
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Tensile stress Artificial neural networks Feature extraction Training Accuracy Neurons Biological neural networks pattern classification Tensor factorization neural network
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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