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240210s2024 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2024.3364157
|2 doi
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|a eng
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| 100 |
1 |
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|a Liu, Risheng
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Learning With Constraint Learning
|b New Perspective, Solution Strategy and Various Applications
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| 264 |
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|c 2024
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| 336 |
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|a Text
|b txt
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|a ƒaComputermedien
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|a Date Revised 06.06.2024
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a The complexity of learning problems, such as Generative Adversarial Network (GAN) and its variants, multi-task and meta-learning, hyper-parameter learning, and a variety of real-world vision applications, demands a deeper understanding of their underlying coupling mechanisms. Existing approaches often address these problems in isolation, lacking a unified perspective that can reveal commonalities and enable effective solutions. Therefore, in this work, we proposed a new framework, named Learning with Constraint Learning (LwCL), that can holistically examine challenges and provide a unified methodology to tackle all the above-mentioned complex learning and vision problems. Specifically, LwCL is designed as a general hierarchical optimization model that captures the essence of these diverse learning and vision problems. Furthermore, we develop a gradient-response based fast solution strategy to overcome optimization challenges of the LwCL framework. Our proposed framework efficiently addresses a wide range of applications in learning and vision, encompassing three categories and nine different problem types. Extensive experiments on synthetic tasks and real-world applications verify the effectiveness of our approach. The LwCL framework offers a comprehensive solution for tackling complex machine learning and computer vision problems, bridging the gap between theory and practice
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| 650 |
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|a Journal Article
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| 700 |
1 |
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|a Gao, Jiaxin
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Liu, Xuan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Fan, Xin
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 46(2024), 7 vom: 09. Juli, Seite 5026-5043
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnas
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8 |
|g volume:46
|g year:2024
|g number:7
|g day:09
|g month:07
|g pages:5026-5043
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|u http://dx.doi.org/10.1109/TPAMI.2024.3364157
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