朱毅
副高级
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[1] 朱毅,周鑫柯,吴信东.Unsupervised Domain Adaptation via Stacked Convolutional Autoencoder.APPLIED SCIENCES-BASEL,2023,13(1)1-1.
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[2] 朱毅,吴信东,强继朋,袁运浩,李云.Representation learning via an integrated autoencoder for unsupervised domain adaptation.FRONTIERS OF COMPUTER SCIENCE,2023,17(5)
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[3] 朱毅,吴信东,强继朋,胡学钢,张玉红,李培培.Representation learning with deep sparse auto-encoder for multi-task learning.PATTERN RECOGNITION,2022,129
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[4] 朱毅,周鑫柯,吴信东.Unsupervised Domain Adaptation via Stacked Convolutional Autoencoder.APPLIED SCIENCES-BASEL,2023,13(1)
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[5] 朱毅,吴信东,强继朋,袁运浩.Representation learning via an integrated autoencoder for unsupervised domain adaptation.FRONTIERS OF COMPUTER SCIENCE,2023,17(5)
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[6] 朱毅,吴信东,胡学钢,张玉红,李培培.Representation learning with deep sparse auto-encoder for multi-task learning.PATTERN RECOGNITION,2022,129
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[7] 朱毅,杨阳,李云,强继朋,袁运浩,张润梅.Representation Learning With Dual Autoencoder for Multi-Label Classification.IEEE ACCESS,2021,998939-98947.
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[8] 朱毅,吴信东,强继朋,袁运浩,李云.Representation learning with collaborative autoencoder for personalized recommendation.EXPERT SYSTEMS WITH APPLICATIONS,2021,186
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[9] 朱毅,李磊,吴信东.Stacked Convolutional Sparse Auto-Encoders for Representation Learning.ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA,2021,15(2)
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[10] 朱毅,李云,岳永政,强继朋,袁运浩.A Hybrid Classification Method via Character Embedding in Chinese Short Text With Few Words.IEEE ACCESS,2020,892120-92128.
