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  "Title": "Discriminant Non-Negative Matrix Factorization",
  "Authors@R": "c(person(\"Zhilong\", \"Jia\", role =c(\"aut\", \"cre\"), \nemail=\"zhilongjia@gmail.com\"),\nperson(\"Xiang\", \"Zhang\", role = \"aut\", email=\"zhangxiang_43@aliyun.com\"))",
  "Description": "Discriminant Non-Negative Matrix Factorization aims to\nextend the Non-negative Matrix Factorization algorithm in order\nto extract features that enforce not only the spatial locality,\nbut also the separability between classes in a discriminant\nmanner. It refers to three article, Zafeiriou, Stefanos, et al.\n\"Exploiting discriminant information in nonnegative matrix\nfactorization with application to frontal face verification.\"\nNeural Networks, IEEE Transactions on 17.3 (2006): 683-695.\nKim, Bo-Kyeong, and Soo-Young Lee. \"Spectral Feature Extraction\nUsing dNMF for Emotion Recognition in Vowel Sounds.\" Neural\nInformation Processing. Springer Berlin Heidelberg, 2013. and\nLee, Soo-Young, Hyun-Ah Song, and Shun-ichi Amari. \"A new\ndiscriminant NMF algorithm and its application to the\nextraction of subtle emotional differences in speech.\"\nCognitive neurodynamics 6.6 (2012): 525-535.",
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