朱毅
副高级
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[1] 朱毅,王书琴,吴信东.Iterative Soft Prompt-Tuning for Unsupervised Domain Adaptation.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2024,36(12)8580-8592.
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[2] 朱毅,耿宜帅,强继朋,袁运浩,吴信东.Self-Adaptive Deep Asymmetric Network for Imbalanced Recommendation.IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE,2024,8(1)968-980.
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[3] 朱毅,汪野,穆建媛,强继朋,袁运浩,吴信东.Short text classification with Soft Knowledgeable Prompt-tuning.EXPERT SYSTEMS WITH APPLICATIONS,2024,246
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[4] 朱毅,耿宜帅,强继朋,吴信东.Representation learning: serial-autoencoder for personalized recommendation.FRONTIERS OF COMPUTER SCIENCE,2024,18(4)
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[5] 朱毅,汪野,强继朋,吴信东.Prompt-Learning for Short Text Classification.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2024,36(10)5328-5339.
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[6] 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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[7] 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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[8] 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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[9] 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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[10] 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)
